Vehicle utilization is defined as the ratio of capacity (weight or volume) that is filled by cargo to the permissible capacity of the vehicle. For companies who use dedicated fleet, have their own fleet for shipments, or use full-truckload shipments (FTLs), improving vehicle utilization is indirectly correlated with shipping costs. It's paramount for such companies to invest in the right optimization tools to improve their vehicle utilization, in order to maximize the RoI on their shipping costs.
However, any technology is as good as the processes it supports. When it comes to optimizing for vehicle utilization, there are several process changes and strategies that one can deploy to improve the efficacy of such tools. In this blog, we will cover 3 such strategies - let’s dive right in.
Set an internal utilisation threshold for your available fleet. Your fleet may have the same size vehicles in the document. But the dimensions of the vehicle may change from region to region. So having an internal threshold means you have the same capacity to be adhered to for loading. Once you have this threshold sent, you can determine the product categories and routes that contribute to max and minimum utilisation of vehicles.
The base concept here is simple - match the products you are shipping to the vehicles you are shipping them. Let me take an example. If you scroll through the available market rates, you will notice that both high volume capacity trucks and high weight capacity trucks demand a price premium. Filling a high weight capacity truck with voluminous materials like diapers, pipes, pharmaceutical pills - will maximize volume. While the volume utilization in this case might be at >90%, the weight utilization will often be <25%. The premium paid for high weight bearing capacity is wasted.
This one is fairly straight-forward - Combine loads for destinations close to each other on a single truck. While doing this is obvious - there are few things that you should define before going for route optimization:
Periodic Load Consolidation
- Set a threshold for maximum pick-ups/ drop offs. This is critical as everytime a vehicle stops, a minimum of 1-2 hours are spent in loading and unloading - adding to the delivery time of subsequent destinations. High number of stops can directly result in delayed deliveries
Distance limiters: Depending on the nature of your business - you would want to limit the distance between two pickup/drop off locations. For instance, I have seen that CPG companies have restrictions on keeping all stops in a single city - to ensure that the vehicle is moving for the most part on highways (faster and efficient), and less on traffic-filled, restricted roads of multiple cities. This helps them in getting their products to the distributors faster. Having pre-defined radius of distance in crucial to effective route optimization
Periodic Load consolidation can happen in two key ways :
Forward Demand Pull (FDP) – ties in the depot/warehouse stock norms with the shipment quantity. This will enable pulling the next expected demand from future to fill a current day’s vehicle to compensate for a vehicle going under-utilised. On the flipside, a utilization threshold can enable the system to drop shipments till the next day in case the current + future date’s demand does not meet the utilization criteria
Permanent Dispatch Planning / Fixed Dispatch Date – like FDP, except that this is pre-decided at a distributor level instead of depot level stock norms. Here, the frequency of stock replenishment of a particular distributor is preempted based on past data. The distributor / retailer is serviced only on specific days in a month.
While the above strategies are internal to a particular company and can help in reducing shipping costs to the tune of 5-15%, there is significantly high potential of further reducing these costs through multi-enterprise collaboration. Think of those high cost, underutilized vehicles you had to ship because they were at risk of service level breach or there was a spike in demand. The above three strategies cannot solve such situations, but multi-enterprise collaboration with other companies can help you do this at a much lower cost.
It allows you to consolidate goods on a vehicle across multiple enterprises (non-competing ofcourse). But this is easier said than done, given the complexity in coordination and collaboration, and limited visibility into shipments of multiple organizations.
The Pando platform is geared to assess the loads moved between two points across its customers, establish demand patterns, suggest combinations based on route, material types, carrier cost and service level commitments, and then provide the execution support to coordinate with the transporters to get these loads placed and delivered. Now isn’t that neat?
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