Parcel delivery: how to deal with increasing volume variability?
- July 31, 2025
- 5 mins
In a context where parcel delivery volumes are becoming increasingly unpredictable, delivery players must constantly adapt to manage this growing variability. This instability affects network performance, complicates route planning, and impacts service quality.
So how can we effectively address these fluctuations while optimizing both costs and delivery times? This article explores the challenges behind this dynamic and presents innovative approaches to structure and manage parcel delivery under these new constraints.
Increasingly unstable parcel volumes: a structural challenge for delivery networks
Since the Covid crisis, parcel delivery networks have been facing unprecedented volume variability, both in intensity and frequency. The pandemic exposed the limitations of existing organizations. Designed to handle relatively stable flows, they struggled to absorb rapid and unpredictable changes in demand.
Today, the rise of B2C e-commerce is amplifying this instability. Unlike B2B flows, which are more concentrated and regular, B2C deliveries are geographically dispersed and difficult to forecast. The trend is global: the number of parcels shipped worldwide is expected to reach 217 billion by 2025, up from 185 billion in 2023, a 17% increase in just two years, according to a Pitney Bowes study.
In this context, transport networks face several major challenges:
Labor shortages: 62% of supply chain leaders rank this as a top operational priority, according to a KPMG study.
Failed first delivery attempts: 1 in 10 parcels fails to arrive on the first try, often due to incorrect or incomplete address data (Loqate).
Rising speed expectations: The global same-day delivery market is projected to grow 11.45% annually between 2025 and 2030, from $32.4B to $54.8B (Mordor Intelligence).
Ambitious climate targets: The European Union aims to cut emissions by 55 % by 2030 — a constraint that requires rethinking distribution models.
Faced with such instability, traditional route planning tools struggle to keep up. They were built for relatively stable volumes, steady teams, and uniform constraints. But last-mile logistics is now a moving target, requiring new agility in how delivery areas are structured.
Between manual management and incomplete digital transformation
Despite ongoing technological advancements, a significant portion of the parcel delivery sector still plans routes manually. Pen and paper, or Excel files, these rudimentary tools remain widely used. These methods are time-consuming, resource-heavy, and leave little room for true optimization.
Other companies have begun digitalizing their operations, but struggle to see real impact. Their tools often ignore critical on-the-ground constraints: routes overlap, zones are unbalanced, and the organization remains inflexible in the face of the unexpected. Simply having data isn’t enough, it must be used meaningfully and consistently.
Shifting from manual processes to data-driven operations is about more than adopting software. It requires deeper transformation, in company culture and field practices. Teams must learn to trust data as much as their operational intuition, accepting that algorithms can sometimes outperform gut instinct.
This transformation demands a clear roadmap, time, and above all genuine commitment to involve teams. Only under these conditions can digitalization become a lever for lasting efficiency, rather than just another layer of complexity.
The solution: smarter sectorization for better deliveries
In this complex context, Kardinal — a recognized expert in last-mile optimization — offers an innovative approach with its solution Territory Analytics & Optimization (TAO). By combining the power of algorithmic computation with a deep understanding of operational realities, TAO helps logistics professionals tackle volume variability with greater precision and resilience.
Finding the right balance between performance and resilience
Sectorization is the foundation of any logistics organization in parcel delivery.
In parcel delivery networks, each driver is assigned a sector or route. In theory, a fully dynamic organization, where sectors change daily, might seem optimal. But in practice, this model remains difficult to implement: parcels arrive very early in the morning, drivers leave quickly to avoid traffic jams, and sorting must be done efficiently. In this context, drivers need to navigate without wasting time, making a minimum level of stability in route organization essential.
Sectorization provides exactly this structuring framework. It helps stabilize processes while absorbing volume fluctuations. However, optimizing sectorization manually is challenging. Reducing the number of sectors limits kilometers traveled and resources used, but sectors that are too large become quickly unmanageable if volumes suddenly increase.
This is the core challenge: finding the right compromise between economic performance and operational resilience. This is precisely what optimized sectorization with TAO enables.
Sustainably structuring territories through “cells”
Kardinal’s approach is based on creating cells, homogeneous geographic units defined through a detailed analysis of the territory and delivery data over a period of several months. These cells incorporate the specificities of each delivery center: maximum/minimum volume or working time, customer types (B2B/B2C), presence of parcel lockers or pick-up points, etc.
Once cells are defined, TAO aggregates them into balanced sectors capable of absorbing volume variations without degrading performance. This structure provides a stable framework while allowing the flexibility needed for daily adjustments.
Indeed, when volumes fluctuate, last-minute adjustments are often necessary: moving a parcel from one route to another, calling in an emergency driver, etc. These ad hoc adjustments generate extra costs, extend delivery times, and increase the risk of errors or failed deliveries.
With poorly designed sectorization, these ad hoc changes become the norm: we have observed agencies where over 50% of routes had to be adjusted daily. Thanks to Kardinal’s TAO solution, these adjustments can be reduced by at least 20%, or almost eliminated in the most extreme cases, without adding routes, simply by reorganizing the territory more intelligently.
Simulating scenarios to better manage variability
Given constant fluctuations in parcel volumes, it is essential to anticipate how these variations impact the organization. TAO allows simulation of postal code transfers between delivery centers, a common practice to balance workloads and optimize resources.
By modeling these transfers, the solution precisely evaluates their impact on volumes to be handled in each sector, the distances traveled, and drivers’ workload. This helps make informed decisions to adapt sectorization and maintain operational performance despite changes.
Additionally, TAO integrates optimization around networks of pick-up points (PUDO) and parcel lockers by simulating the redirection of some parcels to these alternative solutions. This dual perspective allows measurement of the economic and organizational effects of different distribution strategies.
Case study: Kardinal revolutionizes last-mile organization at DPD France
A subsidiary of the GeoPost/DPDgroup, DPD France is one of Europe’s leading parcel delivery companies, with a network of 72 delivery centers handling over 350,000 parcels per day. For the past five years, DPD France has partnered with Kardinal to equip its operational teams with a modern decision-support tool designed to meet the major challenges of last-mile delivery.
Faced with an organization historically based on intuition and field knowledge, DPD France aimed to adopt a more modeled, data-driven approach. The challenge was to support 4,000 drivers (both in-house and subcontracted) in a context of high volume variability and complex operational constraints.
Kardinal’s TAO solution, designed by and for field experts, enabled:
dynamic and optimized sectorization of delivery territories, with fine reallocations of postal codes between delivery centers.
modeling of strategic scenarios such as switching to an electric fleet or reorganizing subcontracted zones.
improved pricing negotiations thanks to precise data shared between DPD and its subcontractors.
better workload distribution among drivers, reducing emergency adjustments and improving service quality.
Thanks to this tool, deployed across 72 delivery centers and used daily by 145 field employees, DPD France has enhanced its last-mile operations management.
Samuel Gangnant, CEO of DPD France, shares his insights: « The first positive effect of implementing Kardinal’s solution is that the teams have embraced the tool, which is extremely important. Today, the teams use the tool on a daily basis to better optimize their routes in their areas. The second positive impact is the improvement in communications with subcontracting partners, which were previously based on elements that were sometimes not very factual. Today, discussions are extremely tangible and shared between our operational teams and subcontractors, which in turn improves communication and collaboration. »
Find more information on how Kardinal’s solution optimizes last-mile deliveries at DPD France.
A gradual rollout designed for real operational impact
Rolling out a solution like TAO isn’t just an IT project, it’s a strategic initiative that must be rooted in operational reality. That’s why Kardinal offers a step-by-step implementation process, built around four key phases, to ensure successful adoption and concrete results.
1. Test the solution with your own data (2 weeks)
The first step is to validate the solution’s capabilities using your real-world data. Starting from a single depot or region, we conduct an initial analysis of your current organization. This quickly demonstrates the added value of the solution on a concrete scope by identifying relevant optimization levers.
2. Define your needs and priority use cases (2 weeks)
Depending on your digital maturity and specific challenges (seasonality, subcontracting, fleet electrification, etc.), we co-define a target scope and realistic action plan. The goal: identify high-value use cases and scope the project effectively.
3. Assess the organizational and economic impact (2 weeks)
A complete evaluation analyzes potential gains (cost savings, driver satisfaction, operational performance, etc.) and the impact on your current setup. This is also the stage where we iterate with your field teams to ensure the solution is well adapted to day-to-day realities.
4. Roll out the solution progressively (2 to 4 months)
The deployment can be done step by step, region by region or depot by depot, to ensure a smooth transition. Rather than changing everything at once, we often recommend starting with a pilot zone, then expanding once results are validated. This gradual approach also helps your teams build skills at each stage.
In just 6 weeks, you’ll be ready to bring AI into your operational planning.
We support you every step of the way, tailoring the process to your level of technological maturity. Because a successful rollout starts with careful planning and is built to last.
Conclusion
With parcel volumes becoming increasingly volatile and delivery networks growing more complex, it’s essential to rethink how last-mile operations are organized. Traditional approaches, whether manual or based on incomplete digitalization, have reached their limits, highlighting the need for flexible, data-driven solutions grounded in operational reality.
The DPD France example shows that intelligent sectorization, combined with a robust tool like TAO, not only stabilizes processes in the face of volatile demand, but also sustainably optimizes costs, resources, and customer satisfaction. This structured, progressive, and collaborative approach, where teams are fully involved, proves to be key in turning variability challenges into continuous improvement opportunities.
In the end, the future of efficient delivery relies on a strong alliance between technological innovation and operational expertise, building organizational agility that can absorb and even capitalize on market fluctuations. Equipping your network with the right tools today means preparing it to meet tomorrow’s logistical challenges while ensuring performance and resilience.
💡Ready to transform your organization and better manage volume variability?
Contact us today to learn how TAO can be adapted to your needs and help boost the performance of your last-mile operations.
