Over the past few years, there have been many technologies that have surfaced to the top of minds within the logistics industry. I like to divide them into three distinct groups.
The first group, Internet of Things (IoT) and Big Data, has the best potential for near-term value creation. IoT technology can produce an incredible amount of data in an automated way; data that pertains to things like shipment location, product condition and more. When this data is combined with transactional, product, and other data sources, valuable insights can be created; and when analyzed over time — this is commonly referred to as Big Data. The number of use cases for IoT and Big Data in logistics is practically limitless.
The second group is comprised of artificial intelligence (AI), machine learning, and robotic process automation. It is still unclear to most supply chain professionals as to the definition of each. In my opinion, AI should be reserved for very advanced use cases, such as automated self-driving trucks. Machine learning is akin to an expert system that can be thought of as artificial intelligence within a specific domain. A machine learning system uses data in a continuous manner to determine better answers. A good example of this is using historical transit data to better predict ETAs in real-time. Robotic process automation is simply good old-fashioned automation, which has been used by enterprise software to automate various aspects of the supply chain for years.
The third is Blockchain. Blockchain applications are underpinned by a technology called distributed ledger. While there are certain use cases within the logistics world that are helped by this technology, many software vendors are applying this technology to solve problems that do not derive any benefit from it. Time will tell if real and valuable Blockchain applications gain traction in this industry.