Road freight is not universally renowned for its investment and move towards cutting edge technologies. Whilst some firms are beginning to understand and invest in areas such as predictive analytics, AI, and machine learning. Many are still over invested in time- consuming, labour-intensive practices that measure historic trends and week old KPI’s.
This article explores how freight firms can leverage the power of data to optimise their operations with a combination of data analytics, AI, and machine learning.
Road Freight Today
The UK’s Transport and Logistics industry accounts for 5.6% of the UK-GDP. Almost 89% of all domestic freight is moved by road using a network of 58,262 road freight enterprises. The industry is heavily regulated and constrained by issues such as congestion, labour shortage and high fuel prices.
The Data Solution
In UK road freight, we often find the same old KPI metrics for measuring performance. Miles Per Gallon (MPG), Cost Per Mile (CPM) and On Time delivery Rate (OTR) to name a few. Whilst the metrics have their place and are indeed useful measures, they are retrospective.
One of the most promising new technologies in the road freight industry is predictive analytics. Rather than looking backwards, this technology, using artificial intelligence (AI) and machine learning to look ahead.
Congestion
The current cost of congestion to UK freight is circa £9.5billion per year. Divided by the reported 535,969 registered HGV vehicles, that equates to an average of £17,758 cost of congestion for each vehicle per year. Utilising real time data to efficiently plan and update journeys can reduce delays and carbon emissions whilst increasing fuel efficiency.
Weather
Drought conditions in the Panama Canal have disrupted shipping, floods have closed roads, storms have also added more uncertainty to supply chain networks. Tackling the weather and effects of it on freight operations is becoming more and more apparent. Predictive analytics can help to reduce down time and optimise operational planning.
Labour
The Department of Transport states that there are currently 271,800 HGV drivers in the UK. The average age of a driver is 53 with 13% of drivers being over 60 years old. Predictive analytics can allow companies to plan their labour requirements in advance. Seasonal variations, holiday and sickness cover or even special projects can be modelled to ensure that freight operations have the optimum staff count required to meet demand.
Fuel Prices
The average mileage undertaken by an HGV is circa 125,000 miler per year. With a fuel economy of 10 mpg and a fuel price of £1.41 per litre, the fuel cost per average mile is circa 52 pence. With volatility in Ukraine and the effect on oil prices, the cost of Diesel has increased and continues to fluctuate. Predictive analytics allows freight companies to ensure that their pricing strategy correlates with these fluctuations in advance, meaning no sudden shock to customers.
Environmental
Road freight transportation and removal services produced 12.1 million metric tons of carbon dioxide emissions in 2022.
Conclusion
The role of data analytics, AI, and machine learning in the road freight industry are vast and can be tailored to individual operational needs. Data led technologies are set to play a huge part in the continued evolution of UK freight. The key message for freight companies is to begin that journey of harnessing and understanding how data can help to evolve and streamline their operations.
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