DPD’s Optimization Journey with AIMMS for Strategic Growth and Operational Efficiency

About the company

DPD (Dynamic Parcel Distribution) Netherlands is a leading parcel service and part of the international Geopost network, Europe’s largest international delivery network. With 12 locations across the country, DPD is among the top three parcel carriers in the Netherlands.

As part of Geopost, DPD Netherlands benefits from a global network operating in more than 50 countries. With a worldwide presence across all continents, Geopost is a key player in parcel delivery and e-commerce solutions with a network of specialized delivery brands, including DPD, Chronopost, SEUR, BRT, Speedy, and Jadlog.

We spoke with Yannick Jacobs, Manager Data Science & BI, and Katinka van de Velde, Senior Data Analyst at DPD, to explore how the company has improved strategic planning, increased operational efficiency, and achieved significant cost savings using AIMMS Optimization Tooling, a complete toolset for building and delivering custom optimization applications.

The Challenge

Before adopting AIMMS, DPD faced significant operational challenges:

• Strategic depot location planning: Determining optimal depot locations was a manual, complex process prone to inefficiencies and higher costs.
• Line-haul complexity: Managing inter-depot transportation was traditionally based on the expertise of experienced planners, relying on manual decision-making rather than automated tools. While effective, this approach made it challenging to efficiently evaluate multiple scenarios.
• Limited internal optimization expertise: Initial optimization efforts depended on external consultancy, limiting the team’s agility and speed.

The Solution

DPD adopted AIMMS Optimization Tooling to build two applications –

1. Long-Range Planning (LRP):

The LRP application was the first major project developed using the AIMMS tooling, focusing on depot optimization. This strategic application determines optimal depot locations, considering variables like delivery routes, transportation costs, and future demand.

AIMMS partner Districon led the initial development of the LRP application, but over time, DPD’s internal team took ownership, building in-house expertise of the AIMMS tooling.

A real estate manager independently ran the Long-Range Planning (LRP) application via AIMMS Cloud (deployment platform), demonstrating strong user adoption.

2. Line-Haul Optimization:

This tactical application streamlines inter-depot transport routes, balancing cost, service quality, and lead time. Direct database integration replaced manual data handling, significantly improving efficiency.

However, adoption challenges arose due to the application’s complexity and a highly detailed set of constraints.

While the model identified millions of euros in potential savings, its successful implementation depended on operational feasibility and the ability to embed it within daily workflows. Additionally, the application faced iterative refinements, as many operational exceptions were not initially accounted for, making it harder for teams to adopt it fully.

The Results and Impact

1. Data-driven decision-making: All investment decisions for new depots are now confidently made using the LRP application. Two depots have already been built based on the application’s insights, and a third is underway, contributing to significant long-term savings.
2. Cost Savings: Strategic depot location decisions have resulted in savings estimated at over a million by optimizing last-mile delivery areas.
3. Operational efficiency: DPD enhanced its AIMMS model by transitioning from Excel-based data entry to database connections for input. This flexibility in data input possibilities helped streamline line-haul planning, enabling more efficient and adaptable data management.
4. Enhanced collaboration and user adoption: Early involvement of key stakeholders ensured high adoption rates and trust in the tool’s outputs. Even non-technical users like real estate managers can run scenarios independently, driving cross-department collaboration.
5. Scalable architecture: While the focus remains on local optimization, LRP application’s scalability presents opportunities for adoption across other GeoPost business units.

“AIMMS (Optimization Tooling) allows us to visualize and validate complex optimization scenarios effectively. Its flexibility in creating user-friendly applications enables both technical and non-technical teams to make data-driven decisions with confidence.”

– Yannick Jacobs, Manager Data Science & BI, DPD

Future Opportunities

• DPD plans to scale AIMMS applications to other GeoPost regions, adapting to local data and processes.
• Use AIMMS for more one-off custom applications to solve unique business challenges.
• Expand sustainability initiatives by leveraging optimization to reduce carbon footprints.

Want to build and deploy custom optimization apps like DPD?