In the ever-evolving world of logistics the race to optimise supply chain operations and enhance overall efficiency is never ending.
This is where FLOX, from Value Chain Lab, emerges as a game-changer. FLOX is committed to overhauling logistics operations by introducing a state-of-the-art supply chain management platform that leverages technology and innovation to drive efficiency, cut costs and foster sustainability.
Our primary focus is on the effective utilisation of shared transportation and warehousing logistics capacities with the aim of streamlining the flow of every order and shipment.
At FLOX we believe in the simultaneous resolution of challenges faced by all stakeholders involved in the logistics chain. This includes not only shippers but also logistics service providers.
Our platform is engineered to tackle a triple-fold dilemma: improving service quality, bolstering profitability and championing environmental sustainability.
FLOX is not just another logistics management platform; it is a state-of-the-art solution that pushes the boundaries of what technology can do for supply chain operations.
By embracing cutting-edge AI technology, machine learning and building our propriety Load Matching Capacity Allocation (LMCA) algorithms, our platform is designed to facilitate seamless collaboration between shippers and logistics service providers, driving unparalleled levels of efficiency and cost savings.
Furthermore, it champions sustainability by encouraging shared transportation.
One of the cornerstones of FLOX's mission is data-driven decision-making. To understand the real-world potential of load collaboration, we harnessed ANPR (Automatic Number Plate Recognition) data from a local English council, spanning five working days.
This analysis focused on three distinct vehicle types: Vans, Rigids and Arctics. The fundamental assumptions revolved around the range of capacity utilisation (from 50% to 95%), identical journey routes and identical starting and ending points for vehicles. The results of this comprehensive analysis are summarised below.
Graph network analysis was employed to reconstruct and analyse the logistical chains within the provided dataset. In this context, a network is defined as a collection of nodes (points) interconnected by edges (lines), amenable to analysis as a graph network.
The camera sightings of each vehicle were treated as the nodes within this network, and their corresponding timestamps provided crucial edge information and directionality for each pair of sightings. After reconstructing individual paths, the findings were amalgamated for a comprehensive path analysis. A bespoke tool has been developed for simulation and path optimisation modelling.
This tool enables users to specify assumed vehicle capacity and define assumptions regarding the number of stops vehicles make in various segments of the route. With this input, the tool calculates both the exact number of identical trips taken and the count of trips with identical start and end points. Utilising mathematical optimisation and user-selected preferences, potential trip-saving opportunities are determined.
The ANPR data allowed us to dissect the potential for load collaboration across these three vehicle types in depth. The first key aspect we examined was the percentage opportunity for savings across the board. Surprisingly, the results demonstrated a remarkable consistency across all three vehicle categories.
At 50% Capacity: When the analysis was constrained to vehicles operating at half their capacity and the journey taking the exact same route, the savings were substantial. In all three categories—Vans, Rigids, and HGVs (Heavy Goods Vehicles)—the number of trips saved stood between 20.04% and 25.07%.
This indicates a significant potential for reducing the number of vehicles on the road and, consequently, fuel consumption and emissions. When we completed the analysis based on vehicles having the same start and end point, the opportunity at 50% capacity jumps to 40.63% to 47.16% Rigids: A noteworthy trend observed in the data was the consistent performance of Rigid vehicles vs vans or HGVs. Regardless of capacity or journey type, the opportunity for rigid vehicles to collaborate was consistently 5% lower than other vehicle types. This could indicate that there might be less overlap in the utilisation of Rigids compared to HGVs and Vans, reducing the opportunity for collaboration.
The most realistic opportunity: It’s commonly understood vehicles are operating at 70% capacity. Across all vehicle types and looking at the exact same route, the collaboration opportunity is between 8.53% and 12.17%. In 2022 lights goods vehicles and HGVS travelled 74.9billion miles Road traffic statistics - Summary statistics (dft.gov.uk). A 10% saving is significant – reducing miles travelled in the UK by 7.49 billion miles.
These findings shed light on the tremendous untapped potential in the world of logistics and supply chain management. By facilitating load collaboration through FLOX, businesses can not only reduce their operational costs but also make significant strides towards environmental sustainability. The platform's innovative approach not only simplifies the process of matching vehicles and routes but also provides real-time visibility into supply chain operations.
With FLOX, shippers and logistics service providers can seamlessly collaborate, harnessing the power of data and technology to drive operational performance. Efficiency, cost savings and sustainability are no longer theoretical ambitions but achievable goals in the logistics world.
In a world where logistics plays a pivotal role in the global economy, FLOX signifies a transformation in the way we manage supply chains. One that is driven by data, technology and a commitment to environmental sustainability. As we continue to navigate the complex challenges of logistics, FLOX will support shippers and LSPS in their ambitions to be more efficient and environmentally conscious.
The data doesn't lie – load collaboration is the way forward. Welcome to the future of logistics, powered by FLOX.