Many of the software trends in mobility and supply chains also affect other industries. That’s because new or upgraded technology has the potential to bring value in many different ways. Below, I’ve tried to capture specific examples to illustrate how tech advancements can improve logistics.
Machine Learning algorithms
Machine learning, or ML, is a major software trend in the mobility industry. In order to understand the benefit it brings, we need to familiarize ourselves with its issues first.
One parameter that affects cross-ocean supply chains is turnaround time. It indicates the time between a vessel’s arrival and its departure. Reducing turnaround time can be very beneficial – port bottlenecks aren’t just an issue of the port itself, they affect the entire ecosystem.
Thankfully, we humans have mastered the art of optimizing our surroundings and work processes to boost effectiveness and improve outcomes. In 2019, Statista reported that the median time container ships spent in ports is around 0.70 days. Japan had the fastest turnaround time of 0.35 days and Australia had the slowest one, with a mean of 1.18 days. This year, experts estimate that the port delays have increased by 11% globally. We can all remember the six-day Suez Canal blockage and its massive consequences. Thus, the reduction of turnaround time by optimizing the port calls (intermediate ship stops) through better planning is a preferred strategy. This is where machine learning algorithms shine the brightest. They help make better predictions of estimated times of arrival (ETAs) and departure. With better ETAs, operations and capacity can be planned better in the harbours, which leads to faster turnaround time.
Holistic decision making
Holistic decision-making is about making decisions based on broader data input. Data can be collected for analysis from various sources: warehouses, transport management systems for roads, air and sea, data from ports, airports, etc. Combining all this information leads to a better decision-making process. Naturally, whenever we have access to more information, we get to minimize risks and secure planned business results.
For example, a company may optimize the processes in a warehouse and then improve transportation processes separately. That will, most likely, yield lesser results compared to optimizing the warehouse and transportation processes based on combined data from both. This principle applied to the whole ecosystem will lead to huge improvements.
Internet of Things (IOT)
Another software trend in supply chain management is the usage of data from IOT sensors. The sensors are used to provide real-time information, which helps optimize the routes of the trucks and reduce transit times. Another use of sensors is to track shipment temperature. This is especially useful for perishable goods and big companies are already using such solutions. For example, global logistics leader DHL is planning to have 10,000 IOT-enabled trucks by 2028.
IoT sensors can also be used for proactive maintenance. The sensors can report potential problems before they actually happen and help the companies plan the maintenance work on the vehicles before they break down. Many experts believe that this is the future of maintenance as it will help companies secure business continuity, and avoid downtimes and financial loss.
With the improvement of AI technology, many companies like Tesla, Uber, or Waymo embraced the challenge to create fully autonomous vehicles. You can imagine how autonomous trucks, for example, can impact the supply chain industry. Smart vehicles won’t need to stop for a break or to get a coffee. As the pandemic showed us, disrupted supply chain shortages can cause lots of trouble, such as empty gas stations and supermarkets. The value of essential workers has also been raising media attention.
A Gartner report from this year regarding transport management systems states that cloud solutions are currently on the rise and dominating. This is triggered by the need for scalability. Scalability is a software system’s ability to increase performance using additional resources. I’ve been observing this trend in our current Dreamix projects as well.
We were discussing a specific use case where printing a label for a shipment takes one second. An implementation detail can, however, increase that time to three seconds. Imagine what happens when you multiply that 2-second difference by the number of shipments a depo processes every day. Now multiply it by all the depos. That’s the kind of time a single code change can cost – or save – a business. That’s why it’s crucial to be able to easily scale applications and be ready for larger system loads.
Those are the trends that I’m familiar with and that I’ve noticed during my work. What other software trends in the mobility and supply chain industry do you know about?