PUDOs and lockers: how to optimize their location for maximum profitability and customer satisfaction?

In a constantly evolving world where e-commerce has grown significantly, and consumer expectations continue to rise, out-of-home (OOH) delivery has become a dominant practice in the logistics and transportation landscape. This innovative approach to parcel distribution relies on a network of Pick-Up and Drop-Off Points (PUDOs) and automatic lockers. The optimization of the location of these OOH points has become a significant concern for carriers due to their potential impact on profitability and service quality. It is important to note that there are two types of OOH networks in this context. First, there are dedicated locker providers such as InPost, who do not operate an at-home delivery network (or a very small one). Second, there are PUDO and locker networks operated by carriers who also provide at-home delivery services.

Currently, there are more than 350,000 lockers in Europe, encompassing providers such as InPost, DPD, DHL, and GLS, and their number could multiply by five over the next five years. Similarly, PUDOs are experiencing rapid growth. Therefore, it is imperative for carriers to address this issue and optimize the locations of their OOH points to remain competitive in a rapidly changing industry. In this article, we will introduce Kardinal’s approach to solving this challenge.

Balancing profitability and service quality: the crucial importance of PUDO and locker location

Strategically positioning Pick-Up and Drop-Off Points (PUDOs) and automatic lockers is a genuine concern for carriers, as it can have a significant impact on their profitability and the quality of service they provide to their customers. This strategic decision is delicate and requires meticulous data analysis, a deep understanding of customer demand, as well as consideration of economic factors.

One of the main difficulties lies in the fact that the location of OOH points must be tailored to customer demand and their practices, including travel time to reach the location, accessibility (such as parking availability and ease of access by foot), and the consumer experience (particularly the transaction time once at the location). These factors can vary considerably from one area to another.

Carriers must take into account the volume of parcels in each region or geographical area, as inappropriate placement can lead to high operational costs and affect accessibility for the delivery vehicle. For example, if too many PUDOs or lockers are positioned in an area with low demand, this can result in unnecessary fixed costs, while a shortage of OOH points in a high-demand area can lead to delivery delays and customer dissatisfaction.

The ideal goal is to position PUDO points and automatic lockers so that they are accessible to all customers within a reasonable timeframe, for example, within 15 minutes of their home. However, this can be a complex task, as it requires taking into account population density, delivery habits, working hours, and other local factors that influence customer visits to PUDOs and lockers.

Man scanning his parcel in front of a locker

When it comes to determining strategic locations for new OOH points, the availability of places also plays a crucial role. For example, in residential areas with few businesses, the installation of a PUDO may be limited, but the introduction of automatic lockers may be more feasible. In contrast, in densely populated urban areas, the placement of lockers may be complex, but it is easier to rely on existing businesses for PUDOs. The capital cost of lockers also needs to be considered: they need to generate significant volumes to ensure a return on investment.

Furthermore, it is important to consider home-to-work commuting flows, as it may be more judicious to place a PUDO in an area with a strong professional presence rather than in a residential area, due to the expected higher foot traffic. Ultimately, these considerations closely align with the principles of geomarketing in terms of location relevance.

From an economic perspective, the profitability of OOH points depends on their utilization. If a pick-up point is underused, it can become a financial burden for the carrier. On the other hand, a highly frequented OOH point can be profitable, but it also requires efficient management to prevent storage limits and resulting delays.

Service quality is also at stake. Poor placement of OOH points can lead to longer delivery times, higher transport costs, and overall customer dissatisfaction. Therefore, carriers must balance profitability with customer satisfaction by finding the right equilibrium in the placement of their PUDOs and lockers.

Carriers face two main challenges: firstly, areas where there are not enough OOH points, and the goal is to identify relevant locations to add them. Secondly, there are areas where there are already a considerable number of OOH points, and in this case, rationalization is necessary to retain only the most effective locations.

Optimizing PUDO/locker location: Kardinal’s approach

Visualizing PUDO/locker coverage

To effectively meet customer demand for out-of-home (OOH) delivery, it is essential to analyze parcel volumes to determine the ideal location of additional PUDOs/lockers. Kardinal has developed a user-friendly application that allows you to visualize this historical data and simulate optimization scenarios, taking into account parcel volumes and the locations of existing OOH points. This application is designed to assist carriers in their decision-making process regarding the placement of future PUDOs or automatic lockers.

Analyzing historical data enables the construction of a predictive model that highlights areas with the potential demand for PUDOs and lockers. This model considers parcels within an area covered by existing OOH points and aims to understand the motivations behind the choice of a point. These motivations include parcel features such as the sender or size, as well as destination attributes such as the type of area and sociodemographic data. This predictive model is then applied to all parcels delivered in the past that were not within the coverage area of existing PUDOs or lockers.

A probabilistic distribution of parcels suitable for OOH points is generated and can be visualized in various ways:

  • Figures by zip code or street on a daily, weekly, or monthly basis.
  • Heatmaps for visually highlighting “underserved” areas with high demand.
PUDO density heatmap

Modeling the optimal location of PUDO/lockers

In addition to heatmaps, users have the option to evaluate potential locations for PUDOs and lockers to determine their viability. This assessment is based on a customizable OOH point profile with various isochrones, representing the time required to reach the pickup point, whether by car, bicycle, or on foot (e.g., 5 or 10 minutes), depending on the carrier’s parameters.

The tool supports two use cases:

1. User already knows the specific locations: In this scenario, the user already has specific locations in mind that they want to assess for suitability. By entering an address and selecting the mode of transportation (car, bike, or walking), the tool displays on the map the extent of points that can be reached within X minutes from that OOH point.

Evaluation of PUDO scenario

2. User seeks relevant location suggestions: Alternatively, if the user wants the tool to propose relevant location suggestions, they can fill in various parameters, including choosing their primary objective: either maximizing the number of OOH points within a given budget or maximizing coverage to serve the largest number of customers possible. The tool generates a list of potential locations, prioritizing those with the best efficiency scores, meaning they offer extensive coverage to reach a maximum number of customers and can handle a high volume of parcels.

New PUDO planning optimization

This functionality enables carriers to make informed decisions to optimize their network of PUDOs and lockers while considering their specific cost and service quality objectives.

In addition to this approach, it is essential to consider the reality of the local economic fabric. This notably includes taking into account the network of existing businesses that could potentially become candidate pickup points and assessing the feasibility of locker installations (a more complex dimension to evaluate). This requires access to very specific third-party information (typically available from geomarketing data providers), which Kardinal can integrate into its analysis.

Optimizing a delivery center's territory considering the PUDO/locker network

For selected candidates, a comprehensive financial impact analysis is conducted by optimizing local sectorization using Kardinal’s Territory & Analytics (TAO) solution. This analysis considers historical data, the current zoning of the territory, and the list of PUDOs/automatic lockers. Scenarios are generated in which certain parcels are redirected to OOH points instead of home delivery, based on their walking distance to PUDOs/lockers and the probability derived from the global model.

PUDO comparison in TAO

This optimization provides insights into the new sectorization with these OOH points and their potential impact (organizational and economic) on deliveries, allowing for comparison with the actual situation. This process assists carriers in making informed decisions on the strategic location of PUDOs and lockers, ensuring efficient service delivery while maintaining profitability.

Learn more about Kardinal

Kardinal develops innovative technological solutions to support parcel delivery providers in optimizing last-mile operations. Based on historical data and operational constraints, Kardinal’s solution recommends the best territorial organization for each geographical area. The algorithms employ advanced mathematical techniques and machine learning to accurately determine the most efficient delivery zones in the long run.