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  • Graham Wilson

Modern Analytics in Logistics; needed to meet the challenges of an ever evolving industry.

The logistics market has seen an unprecedented boom in recent years. In the UK in particular, close to 200,000 companies operate in the logistics industry, employing a staggering 2.5 million people. The challenges brought upon by the COVID-19 pandemic and the post-Brexit landscape contributed to a rapid expansion in fleet digitalisation, with certain logistics sectors expecting a dramatic increase in coming years. The use of rail freight, for instance, has been steadily increasing in the UK, with a 3% annual rise in 2021. Network Rail forecasts that the rail freight sector could see an increase by around 30% by 2035 (provided the necessary capacity is made available).

However, while recent years and the boom of e-commerce have led to a surge in the demand for logistics services, the COVID-19 pandemic also showed major players another side of the industry and highlighted the importance of meeting modern challenges with modern solutions, namely technology. The pandemic-related disruptions revealed the weaknesses in supply chains around the world, emphasising the need to develop more resilient supply chains and come up with recovery plans. Often, these plans rely on technology.

Modern technology, no longer a luxury but a necessity

We’ve already seen a boom in the use of technology across the logistics industry. Artificial Intelligence and Augmented Intelligence, for example, are already widely used across sectors with demand and usage expected to continue increasing throughout the next years. Augmented Intelligence solutions allow professionals in the field to perform their duties faster and more efficiently while reducing costly mistakes and realise significant savings. However, if they highlight one thing is that modern technology is no longer a luxury but a necessity to stay competitive in an aggressive market such as the logistics one.

Yet, a number of small and medium UK logistics businesses still rely predominantly on manual reporting. Relying on manual processes to estimate key performance indicators doesn’t only incur additional expenses (in terms of time, as well as money), but is also more likely to lead to costly mistakes.

The UK logistics market is seeing an unprecedented increase in the demand for digitalization of the fleet service: meaning, companies are starting to rely more and more on modern analytics tools. Take performance analytics, for instance. These tools allow manufacturers to set up metrics measuring performance and gain a better understanding of how different aspects of their company are doing. This is essential for companies looking to diversify and decentralise their supply chains in 2022. Working with multiple distributors means inconsistencies in reporting, variation in freight prices, and other factors that might make it difficult to determine whether there was a profit or loss on a particular shipment. Performance analytics can help you understand if your targets were met or missed, and diagnostic analytic tools can further provide insight into why these targets might not have been fulfilled. Unfortunately, none of this is possible if your company relies on “old school” manual reporting.

Analytics for supply chain

Circling back to supply chain resilience, to stay adaptable, supply chains need to have enhanced visibility, dynamic freight procurement options, and reliable analytics that allow for speedy, effective decision making. All three of these, but particularly analytics require digitisation. For years, data in the industry has been siloed, with fragmented ecosystems and massive inefficiencies being the norm rather than the exception. Digitising operations is the single most effective solution to improving the resilience of supply chains and staying competitive in the market.

Analytics are also becoming smarter to serve the growing needs of the industry. Start-ups are focused on creating products that leverage predictive and advanced analytics to give logistics companies a competitive edge. The first step—and often the biggest challenge these companies face—is getting clean digital data. But advanced analytics are essential to ensure better supply chain visibility, predictive maintenance, detection of unexpected conditions and demand forecasting, all of which ensure the resilience of the supply chain.

Another significant challenge 2020 unravelled was single-source dependency. When China’s manufacturers shut down in the wake of the COVID-19 pandemic, this triggered a snowball effect and as more countries placed restrictions on border entry, this further slowed down supply chains. As a result, those manufacturers who relied too much on partners or suppliers in a single country, experienced serious delays… and that of course meant significant costs as well. The solution to this challenge is simply: diversifying and decentralising. To achieve this level of agility, however, a company needs a good digital strategy. Modern digital solutions enable sourcing models that are far more adaptable and sustainable.

Sustainability, a major challenge for logistics companies

Speaking of sustainability, it has been and still is one of the major challenges logistics companies face. Inefficient routes or half-full trucks can put a dent in the bottom line of every manufacturer. Optimisation of routes is essential, and the simplest solution is by digitising the supply chain. Route optimisation algorithms use data such as historical delivery routes, fleet management data, road maintenance and personnel schedules and anticipate delays. They can also suggest faster routes for deliveries. A digitalised supply chain can also help with meeting increasing consumer demand for more eco-friendly options. Customers are now eager to know where their products come from and being able to trace parts or ingredients back to their source can have a significant impact on their purchasing decision. Modern analytics can not only optimise and improve logistics routes and reduce half-full trucks but can also help a manufacturer provide reliable information about the source of their products, thus satisfying consumer demand.

But advanced analytics goes beyond simply improving routes. Predictive analytics, on the other hand, are essential for forecasting future trends in order to remain competitive. Tools relying on predictive analytics rely on historical data to build predictive models, optimising inventory, routes or improving anticipatory shipping. A company that might not have the inventory at the time an order is placed risks delays on order fulfilment. Over-reliance on manual reporting can easily result in surplus of inventory which incurs greater warehousing costs. The simplest solution is to improve supply chain visibility, and the easiest way to do so is by employing modern predictive analytics. What’s more, in addition to ensuring you have a complete visibility of your current inventory, modern digital tools can also inform supply chain management of an incoming surge or dip in demand and thus, lead to better decision-making.

Thriving in an ever evolving industry

As an increasing number of customers turn to e-commerce and online shopping, anticipating their needs could be just what a logistics company needs to stay not only afloat but thrive in a competitive modern-day market. Amazon, for instance, relies on powerful anticipatory shipping analytics tools: they estimate when a customer will place a new order based on their past purchasing behaviour. In turn, this gives the manufacturer time to prepare and plan their inventory and shipments in advance, ensuring less waste, more on-time deliveries, and greater customer satisfaction.

In the past few years, the UK logistics market has enjoyed significant growth. But to remain competitive within this rapidly evolving and growing field, manufacturers and logistics professionals need to address the major challenges their companies face. By leveraging the power of modern analytics tools, the logistics industry can significantly improve operations, from route optimisation to forecasting to greater supply chain visibility and significantly reduced waste.

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