Humans are prone to exaggerate, use hyperbole, and/or sensationalize to gain attention. The term “revolutionize” is often used in such a way. According to the Cambridge Dictionary, to revolutionize something is “to make a big change or improvement to the way something works or looks, or to the way that people do a particular activity.” Many pundits claim new technologies are revolutionizing or transforming logistics. Based on the dictionary definition, they are correct. Kushal Nahata (@kushalnahata), CEO and Co-founder at FarEye, writes, “The need to deliver on rapidly evolving customer expectations and simultaneously ensure profitability are driving businesses to rethink the way they have been executing supply chain and logistics operations. Achieving this twin objective is not easy. To address this, savvy businesses have been experimenting with multiple disruptive technologies for quite some time now, hence opening the doors to solutions that are driven by technologies like machine learning, the Internet of Things (IoT), automation, data analytics and more.” Revolution and disruption are generally traveling companions. Like Nahata, Gurcharan Singh, Founder of LogixGRID Technologies, believes disruptive technologies are transforming the logistics arena. He asserts, “Logistics, … in this era of the profound transformation, … is becoming one of the most disruptive fields across the globe.”
Disruptive technologies transforming logistics
Before discussing how technology is changing logistics, let’s discuss the disruptive technologies referred to by most pundits. They include artificial intelligence (AI) and machine learning, the Internet of Things, advanced analytics, sensors, automation, robotics, and blockchain. These technologies generally have one thing in common: Big data. Mona Lebied writes, “Big data is revolutionizing many fields of business, and logistics analytics is one of them. The complex and dynamic nature of logistics, along with the reliance on many moving parts that can create bottlenecks at any point in the supply chain, make logistics a perfect use case for big data.” She notes logistics providers have numerous sources from which data is drawn, including: Traditional enterprise data from operational systems; traffic & weather data from sensors, monitors and forecast systems; vehicle diagnostics, driving patterns, and location information; financial business forecasts; advertising response data; website browsing pattern data; and social media data. She concludes, “It looks like the future is bright for logistics companies that are willing to take advantage of big data.”
Cognitive technologies. Taking advantage of big data generally means leveraging cognitive technologies (i.e., cognitive computing, which includes machine learning and embedded analytics suites), like the Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act and Learn®. Kayla Matthews (@KaylaEMatthews) explains, “AI allows companies to successfully predict future scenarios, highlighting and responding to patterns in the supply chain with the help of big data. With big data, companies are able to make predictions with greater accuracy, and in conjunction with AI, it can improve the transparency of the supply chain and optimize delivery routes.”
The Internet of Things. Nahata writes, “The world of logistics has now been exposed to a vast pool of smart IoT-enabled devices. The number of these IoT-enabled devices has been increasing at a fast pace and is forecast to reach up to 30 Bn by 2020. The deployment of IoT powered solutions will continue to transform and modernize the supply chains by enhancing the operational efficiencies and increasing visibility.” As Nahata implies, pundits often use the term IoT as shorthand for a broader ecosystem consisting of sensors at one end, connected via the IoT to advanced analytics platforms on the other end.
Automation and robotics. The rise of e-commerce and promises of fast delivery have placed enormous pressure on logistics providers. To meet the needs of today’s business environment, supply chain stakeholders have increasingly turned to automation and robotics. Matthews explains, “The supply chain is starting to make greater use of robotics in the warehouse environment. Using AI, robots are able to track and locate the inventory. The robots can then move the inventory through the warehouse in order to make the process more efficient for other workers. These machines work through deep learning algorithms that can help them make autonomous decisions related to their duties within the warehouse. With the assistance of robots, other workers now have more time to do higher-value tasks because the time-consuming duties they usually had to perform are now automated.”
Blockchain. Supply chains have become enormously complex and tracking resources and goods along the supply chain has become extremely difficult. Many observers believe blockchain will help provide a solution. Sean Culey, an adviser with the Association of Supply Chain Management, explains, “Blockchain’s primary use will be focused on supply chains where it is important to record the source of the goods and track the goods, such as the food and perishable goods industries.” Andrew Dawson, a commercial director at MACMobile, adds, “Blockchain is a simple technology, which has various flaws, but we predict that its evolution will provide value for supply chains and will become a feature of supply chains.”
How technology is changing logistics
Lebied discusses five ways logistics operations are changing as a result of disruptive technologies. They are:
1. Improved last mile delivery. Last mile delivery is the most important and, often, the most expensive part of logistics. Lebied writes, “The last mile of a supply chain is notoriously inefficient, costing up to 28% of the overall delivery cost of a package. … Because of the low cost and ubiquity of fast mobile internet and GPS enabled smartphones, as well as the spread of the Internet of Things through sensors and scanners, shippers are able to see how the delivery process goes from start to finish — even during the last mile.”
2. Improved reliability. Lebied writes, “As sensors become more prevalent in transportation vehicles, shipping, and throughout the supply chain, they can provide data enabling greater transparency than has ever been possible.”
3. Improved route optimization. Lebied rhetorically asks, “Why are logistics companies so interested in optimization?” Her answer, “For two reasons: it helps them save money and avoid late shipments. When you’re managing a delivery system or supply chain, you have to walk a fine line between overcommitting resources and vehicles and undercommitting them. … To add to the challenges of optimization, the factors involved in effectively allocating resources are constantly changing. Fuel costs can change. Highways and roads can be temporarily shut down or new ones can be built. The number of vehicles at your disposal may change due to repairs or new acquisitions. Weather conditions, both seasonal and immediate, are constantly changing. Big data and predictive analytics give logistics companies the extra edge they need to overcome these obstacles.”
4. Improved shipping quality. Lebied writes, “Keeping perishables fresh has been a constant challenge for logistics companies. However, big data and the Internet of Things could give delivery drivers and managers a much better idea of how they can prevent costs due to perished goods.”
5. Improved warehousing operations. According to Lebied, “Big data combined with automation technology and the Internet of Things may make logistics an entirely automated operation. Big data allows automated systems to function through intelligently routing many different data sets and data streams.”
Matthews concludes, “It’s evident that AI has been able to help businesses in a variety of ways, and it will only continue to develop as time goes on and companies become more knowledgeable about its capabilities. The opportunities are endless, and it is certain that the shipping and logistics business will look completely different in the years to come.” Lebied adds, “We’re on the cusp of big data transforming the nature of logistics. Big data in logistics can be used to reduce inefficiencies in last mile delivery, provide transparency to the supply chain, optimize deliveries, protect perishable goods, and automate the entire supply chain. Logistics companies are aware of these possibilities, and are striving to make more data-driven decisions moving forward.” I don’t think it’s hyperbole to conclude disruptive technologies are revolutionizing logistics.
 Kushal Nahata, “Revolutionizing Supply Chain Logistics With IoT And Machine Learning,” Inc42, 31 August 2019.
 Gurcharan Singh, “How Artificial Intelligence and Machine Learning Are Revolutionizing Logistics, Supply Chain and Transportation,” Entrepreneur India, 8 June 2019.
 Mona Lebied, “5 Examples of How Big Data in Logistics Can Transform The Supply Chain,” The datapine Blog, 5 April 2017.
 Kayla Matthews, “5 Ways AI Is Changing Shipping and Logistics,” Datafloq, 16 August 2019.
 Schalk Burger, “How technology is starting to change logistics ecosystems,” Engineering News, 19 July 2019.