Amazon's logistics network in Europe and North America struggles with geographic data inaccuracies affecting operations. This thesis presents a new algorithm to fix these errors, improving the internal graph representation of Amazon's network, crucial for internal optimization models. Amazon started as an online bookstore and evolved into a global e-commerce, cloud services, and AI leader through innovation and reinvestment. Its efficient supply chain ensures quick deliveries. The EU Supply Chain Science team optimizes Amazon’s supply chain, using machine learning and optimization models to enhance operational efficiency. Within EU SCS, the True North project creates an end-to-end Sales and Operations Planning plan, optimizing speed and cost of delivery by using forecasted demand at the ZIP code granularity to plan workforce allocation and transportation connectivity.