How Santa Optimizes His Warehouse Network?

Every December, Santa’s team gathers in the North Pole operations center to analyze global demand. Gift requests shift year by year, new regions become more active, and delivery expectations continue to rise.

This year, Santa noticed significant changes in the distribution of “customers” across the world. Some regions have grown rapidly, others have become more complex to serve, and reindeer travel time is becoming a more important factor to consider.

So the big strategic question emerges:

Where should Santa place his next regional warehouse to improve delivery times and reduce travel distance?

In other words, it identifies where a facility should be located if the goal is to minimize distance or effort relative to demand, making it an effective first estimate before more complex models are run.

To answer this, Santa begins with a classic starting point for network design: the Center of Gravity method.

His analysts compile global “customer” data – assigning weights based on demand levels, density, and delivery needs. This allows them to model where a new location might best serve the majority of recipients while keeping travel distances manageable.

Santa’s goal at this stage is not to finalize the perfect distribution strategy. Instead, he wants a simple, clear, and data-based starting point that helps him understand how different factors shift the ideal location.

As Santa explores potential warehouse locations, he also evaluates different modeling approaches.

A recent addition to his toolkit allows him to enable or disable a “Minimize Distances” step in the analysis:

With the toggle OFF:
Santa gets a pure weighted average center, a quick calculation ideal for early explorations.

This flexibility allows Santa to test multiple scenarios efficiently:

• What happens if we prioritize demand density?
• How does the optimal point shift when minimizing actual travel distances?
• Does a refined optimization significantly change the candidate location?

In many cases, he finds that even small adjustments in customer distribution lead to meaningful changes in optimal placement – exactly the kind of insight that informs smarter decisions.

As Santa reviews his maps and models, he can’t help but think about how much impact the right warehouse location can have in the real world. Studies show that placing facilities closer to demand centers can reduce total logistics costs by 10-30% and improve delivery times by 15-40%,  numbers that even make Santa raise an eyebrow.

He also knows that last-mile delivery can account for over half of total logistics costs, which suddenly makes the reindeers’ long overnight routes feel all too familiar. And with nearly half of distribution companies reporting increased pressure to deliver faster, Santa realizes he’s not alone in facing rising expectations. These facts remind him why a simple Center of Gravity analysis is such a powerful first step before moving toward more advanced planning.

Santa’s seasonal planning highlights a broader truth in supply chain strategy: You don’t always need complex network optimization tools to get meaningful insights.

A Center of Gravity approach is often the ideal first step when exploring expansions, evaluating service-level improvements, or analyzing new market regions. It provides clarity, direction, and a strong starting point – before moving into more advanced modeling.

For Santa, it helps ensure timely deliveries across the globe. For supply chain teams, it offers a fast, structured way to identify where new facilities can create the most value.