Unlocking Hidden Potential in Linehaul
How data-based analyses help to make consolidation potential visible in linehaul
Many linehaul networks function reliably in everyday operations. Schedules are set, processes are in place, and routines are well-established. And yet, upon closer inspection, it often becomes clear: not everything that works is truly efficient.
What causes this – and how can existing structures be purposefully questioned?
We're talking about this with Christina Gödecke, Senior Account Executive at OPTANO, who in her daily work deals with the analysis of logistics networks and the challenges of modern transport planning.
You are very active in the market and regularly speak with decision-makers in the logistics industry. What topics are currently shaping discussions?
High energy costs, increasing sustainability requirements, and intense competition are putting significant efficiency pressure on many transport networks, whether in the courier, express and parcel sector or in general cargo and less-than-truckload transport. At the same time, classic cost-reduction programs have long been implemented in many companies.
Nevertheless, practice repeatedly shows: Consolidation potential often remains undiscovered, especially in the main process. Networks have grown over years, dependencies are complex, and in day-to-day operations, transparency is often lacking to systematically identify inefficient structures.
Making such potentials visible is precisely one of the ways to achieve additional savings in the short term.
Many companies have been successful in the market for years, and their employees have a lot of experience. So, if we say that consolidation potential in the main process is often not fully utilized, it sounds daring at first. Or does it?
We do not presume to know better than the experts within the companies. Rather, our goal is to create additional transparency and provide decision support.
Many inefficiencies are not immediately visible in day-to-day operations. Structures with low utilization, redundant routes, or unnecessary parallel traffic are more common than expected in real networks.
One reason for this is that data is often not centrally available or is not specifically used to create transparency. At the same time, many networks have grown historically and are continuously changing. Under these conditions, keeping an overview and identifying inefficient structures with the least possible effort is a real challenge for planners.
„Many inefficiencies in linehaul networks are simply not visible in daily operations.“
OPTANO is known for sophisticated mathematical optimization solutions. However, the Linehaul Analyzer is intentionally designed as an entry point into data-driven optimization of linehaul networks. What exactly does the Linehaul Analyzer do and what overview does it provide to planning managers?
The first step is transparency. The Linehaul Analyzer creates a clear overview of trips, utilization, and associated costs. With just a few data points, inefficiencies and redundancies in the network can be made visible. The algorithm analyzes existing schedules and specifically identifies trips that can be consolidated.
The system makes concrete suggestions on which connections could be merged and how these changes would affect the network. This provides planning managers with a data-based perspective on structures that are often difficult to discern in day-to-day operations.
The Linehaul Analyzer does not replace humans. Rather, it supports decision-making. Suggestions can be reviewed, commented on, accepted, or deliberately rejected. In this way, the Linehaul Analyzer combines the experience of planners with the transparency and analytical capabilities of a data-based system.
„The linehaul analyzer does not replace humans; it makes structures visible that were previously hidden.
The Linehaul Analyzer deliberately works with minimal data and focuses on key levers in the network. Where are the limitations of this approach?
We consciously work with a simplified model of the network in the Linehaul Analyzer. The focus is on the schedule, capacity utilization, and costs. This allows for a very quick analysis of potential consolidation opportunities. At the same time, however, this approach means that more complex dependencies are initially not taken into account.
In more comprehensive transport optimizations, for example, shift times at transshipment points, different lead times for individual products, or other operational restrictions can be modeled. The Linehaul Analyzer deliberately forgoes this level of detail to enable a quick and pragmatic start.
This is a major advantage, especially for organizations with little prior experience in data-driven optimization. This allows initial potential to be made visible with manageable effort. If networks are to be analyzed in more detail or fully optimized later, additional dependencies and constraints can be taken into account. In such cases, the more comprehensive optimization solutions from the OPTANO portfolio are used.
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The principle sounds understandable, but it still feels a bit like a black box. Can you explain with a concrete example where the Linehaul Analyzer makes adjustments and what that means in practice?
Sure: Let's consider a start-destination relationship on which multiple trips take place per day. At the same time, temporally similar connections exist between spatially close locations.
For example, in the Linehaul Analyzer, it can be specified how much departure or arrival times may shift in order to create additional consolidation opportunities. Likewise, it can be defined how much detouring from an existing route is acceptable. Further parameters include, for example, the maximum length of a consolidated route to avoid overly short multi-stop trips, the average travel speed, or the duration of a stop.
Based on these settings, as well as cost rates and distance information, the system analyzes which connections can be sensibly combined. This can result in different variants. In some cases, it is proposed to cancel a trip entirely if the entire load can be shifted to a later connection with an identical route. In other cases, multi-stop connections are created, where routes to nearby locations are merged into a single trip.
The result is initially an overview of possible consolidations. For a canceled trip, there are often several alternatives that planners can choose from.
If an option is accepted, the system recalculates the impact and adjusts available capacities accordingly. This allows you to work through possible changes step by step. If there is still uncertainty, suggestions can be commented on or saved for a later decision. Notes for colleagues can also be added directly.
In the end, an overview of all accepted changes is created, which can serve as a basis for adjusting the schedule.
OPTANO has gathered extensive experience in optimizing logistics networks through many projects. How does the Linehaul Analyzer fit into this portfolio, and for which user group is it particularly intended?
A large part of our solutions aims to map complex logistics and distribution networks as completely as possible. Numerous dependencies within a network can be taken into account.
We are convinced that the actual optimum often only becomes apparent when a network is comprehensively modeled. At the same time, however, we also know that such optimizations require a certain level of maturity. Companies must first have sufficient data and be able to provide it in a quality that enables reliable results.
If this can unlock significant savings, then the effort is naturally worthwhile. However, in practice, we often see that companies first want to build trust before investing in extensive data preparation. This is precisely where the Linehaul Analyzer comes in. It allows for an easy start, with which initial potential can be made visible, thus building trust in mathematical optimization.
The solution is therefore particularly suitable for companies that have had little contact with such approaches so far and want to start pragmatically. If the need grows later, this entry can be easily expanded, as our portfolio includes numerous further optimization solutions.
How can companies tell if their linehaul schedule is worth reviewing? Are there typical signs of untapped consolidation potential?
Analyzing the network can be worthwhile, especially when schedules are rarely adjusted holistically but are mainly supplemented or adapted locally or based on customer demand.
If consolidations are also predominantly planned using spreadsheets or based on experience, a closer look is almost always worthwhile. Especially in such cases, interdependencies in the network often remain hidden.
The first step is deliberately kept simple: a conversation. Not with the goal of selling, but initially to understand how the respective network is structured and where potential starting points might lie.
People from Ostwestfalen, where OPTANO comes from, are considered down-to-earth and pragmatic. That's exactly how we approach such topics. It's not about sales rhetoric, but about solving real problems.
„Often, a look at a typical week is enough to make initial consolidation potentials visible.“
What are the prerequisites for companies that want to try the Linehaul Analyzer, and what is the typical effort involved?
The requirements for use have been deliberately kept low.
Essentially, we only need the current timetable and rough utilization data, for example for a typical week. Approximate percentage utilization of the vehicles is often sufficient.
If shipment data with volume information is available instead, this can of course also be used.
We load this data into the Linehaul Analyzer and perform an initial analysis. Subsequently, the parameters can be adjusted step by step and the results iteratively refined. Often, after an initial discussion, we look at a sample week together and analyze the network. This allows us to quickly identify potential opportunities.
Linehaul networks are complex and have often grown over years. This makes it all the more difficult to maintain an overview of potential consolidation opportunities in day-to-day operations. This is precisely where data-based analyses can help to systematically question existing structures and open up new perspectives on familiar schedules.
Anyone who wants to look at their own network from this perspective can do so together with us.