Gary Dodsworth explores how the freight industry is harnessing the value of Big Data and discusses what other sectors can learn from its lead

Big Data has been a prominent area of discussion within the logistics industry since 2013, when the Annual Study on the State of Logistics Outsourcing declared data-driven decision-making as essential to the future success of all supply chain activities. The 21st Annual 3PL Study* built on this view, with research suggesting that 98 per cent of 3PL logistics businesses believed Big Data to be ‘essential to the future success of supply chain activities and processes’.

Big Data and why it’s relevant
So, while Big Data isn’t necessarily a new phenomenon, it’s still a relatively new idea for many businesses and, as such, can feel like a minefield. However, due to its invaluable wealth of information, more and more industries are investing in this type of data, and logistics is no exception.

The analysis that comes from Big Data, turning it into actionable data, allows organizations to identify new opportunities and maximize efficiencies. For example, the Rhenus Group uses fuel management systems to track product flows. With a wealth of knowledge at our fingertips, looking into this data archive can help us (and other forwarders) plan ahead for seasonal spikes. At Rhenus, we use data from the past three years to help understand annual trends and mitigate against potential issues.

The value of actionable data has been apparent to many leading logistics businesses for some time, with a number of big industry players already having robust strategies in place. However, as logistics management and transportation networks become larger and more complex, driven by demands for more intricate service levels, the type of data managed also becomes more complex. In order to remain competitive, logistics companies must work to continuously update and maximise their data capture.

At the forefront of Big Data
At its core, Big Data refers to massive or large-scale data that can be analyzed to reveal patterns and trends that assist with forecasting and decision making throughout the supply chain. By combining historical data, real-time information and customer insights, businesses are able to take a proactive approach to decision-making; streamlining the supply chain as well as preparing against external disruptions. Outlined below are a few key areas in which Big Data can optimize the supply chain:

• Using data to determine the most efficient routes for planning and traffic management saves on delivery times. For example, avoiding key roads during rush hour and hot spots for congestion allows the transportation of goods to have a more accurate delivery time while minimizing carbon emissions
• With warehouses being a core part of the business for many logistics firms, space is key. Interpreting Big Data can optimize transportation management plans, ensuring that warehouse space is used effectively – keeping the flow of products in and out of the warehouse moving smoothly, thus saving time and money
• Data can also enable businesses to boost their bottom line, allowing budget decisions to be made based on evidence. For example, streamlining routes will lead to a decrease in fuel, meaning both money and time can be saved. It can also capture buying patterns over a period of time, and help you predict what you need to order and when (eliminating unnecessary spending)
• Data can mitigate against external disruptions, whether it be weather analysis and road conditions, or leveraging accurate traffic forecasting to time your shipments and streamline routes to include detours and off-peak days. Proactive analysis of social events such as parades, festivals and rallies can be sourced from news and social media to provide valuable information about routes to avoid
• Through streamlining all areas of the day-to-day, businesses will naturally reduce their environmental footprint – something all industries are striving for

It is this data interpretation and the monitoring of product flows across the globe that enables the logistics industry to proudly sit at the forefront of the data curve.

However, logistics businesses don’t always utilize their strong position. While many may be ‘clued-up’ on all things data, partners and customers (especially those in manufacturing) may not be. The responsibility lies with the sector to share this knowledge. Through experience and previous success, our industry finds itself uniquely positioned to influence other sectors, encouraging the adoption of data processing.

Industry examples
The use of actionable data isn’t new to Rhenus. Our Freight Industry Solutions team in Germany has been recognized for its pioneering work in this area. Full automation is achieved through our in-house, custom-built transport management system, used to align various processes and transports across the globe. This system empowers the customer to access accurate real-time tracking for their goods across the entire supply chain, ranging from order management to accounts. The Rhenus supply chain is transparent and maintained in such a way that logistics costs can be easily analyzed and reduced.

We have a responsibility as the front runners to share and teach other industries how best to utilize and implement the principles of harnessing Big Data. The only question that remains is ‘are you ready to help’?

* http://www.3plstudy.com/3pl2020download.php
Gary Dodsworth is Road Director at Rhenus Logistics UK. The Rhenus Group is a leading logistics service provider with global business operations and an annual turnover of EUR 5.5 billion. Rhenus has business sites at 750 locations worldwide and employs 33,000 people. The Rhenus Group provides solutions for a wide variety of different sectors along the complete supply chain; they include multimodal transport operations, warehousing, customs clearance as well as innovative value-added services.
www.rhenus.group