Optimizing Supply Chain Distribution Networks: Lessons from a Large-Scale Project

In today’s complex business landscape, supply chain optimization is crucial for reducing operational costs and ensuring timely deliveries.

I’d like to share some insights from a recent project we undertook for a multinational company, with over 2,000 service points across neighboring countries, 10+ existing warehouses, and an annual distribution cost exceeding €20 million.

The Challenge: Finding the Optimal Distribution Network

The company’s management tasked us with a clear objective:

• Identify the best possible warehouse locations based on the existing service network, product types, and store replenishment needs.
• Estimate operational costs to support data-driven decision-making.
• Explore alternative growth scenarios to future-proof the network.

Our Approach: A Data-Driven Methodology

To tackle this challenge, we followed a structured methodology:

1. Identifying optimal geographic locations for distribution centers based on the existing network.
2. Evaluating fleet requirements, including total kilometers traveled, driving hours, fuel consumption, and calculating annual transportation costs.
3. Assessing warehouse operations costs, focusing on storage and dispatch management.

The Data Challenge: A Crucial First Step

Our journey began with an in-depth analysis of the available data from the past 12 months, covering:

• Store-level demand,
• Warehouse operations,
• Transportation metrics.

Building an accurate model of the existing operations was the most time-consuming aspect of the project. Data quality issues posed significant hurdles, requiring cleansing and validation to ensure reliable insights.

Key Insights and Results

After four months of analysis, we successfully developed a comprehensive model that:

• Provided a clear view of the current cost structure and operational dynamics.
• Enabled us to run optimization scenarios with confidence.

With solid data in place, determining the optimal warehouse locations became a more straightforward process. The cost estimation of transportation operations also proved to be relatively simple, thanks to our well-structured model.

Takeaways for Supply Chain Professionals

1. Data Quality is Paramount: Investing time in data cleansing and validation is critical to building reliable models.
2. Optimization Becomes Easier with a Strong Foundation: Once a solid operational model is in place, scenario testing and decision-making become more effective.
3. Future-Proofing the Supply Chain: It’s important to continuously evaluate and adjust the network to accommodate future growth and changing market conditions.