With the increase in demand and growth, companies in the Last-Mile Delivery and Logistics sector are beginning to explore Artificial Intelligence and automation to cope with the challenges faced in their operations.
The last-mile delivery and logistics sector has become one of the fastest-growing sectors in the world with the help of globalisation and growth in the regional uptake of e-commerce products and services. The global Last-mile delivery market size was valued at USD 18.7 Bn in 2020. Furthermore, the global last-mile delivery market revenue is expected to rise to $117.9 billion by 2030, demonstrating a CAGR of 20.3% from 2020 to 2030.
With the increase in demand and growth, companies in the sector are beginning to explore many up and coming technologies like Artificial Intelligence and Automation to cope with the challenges faced in their operations.
Continuing reading to find out how!
Top Challenges faced by companies in the last mile delivery sector:
1. High Delivery Cost: Providing a great delivery experience while remaining profitable is a challenge for retailers and logistic companies. Up to 28% of the delivery cost comes from the last mile part alone. One of the main reasons is a lack of infrastructure to deliver products on time. Additionally, failed delivery attempts, long routes, driver salary, and fleet operations significantly impact the delivery cost.
2. Lack of Transparency: Buyers want to know the exact location of their product and the expected delivery time. As a result, visibility is the most significant prerequisite to developing credibility.
3. Unpredictable Elements: Traffic, weather conditions, and flat tyres are some last-mile problems that are beyond human control. The only thing logistics companies can do is seamless communications and create a plan B to deliver products quickly.
4. Inadequate Route Planning: Inefficient route planning is the major reason for late deliveries.
In many cases, the root cause for the first and second challenge of high delivery cost and lack of transparency comes from the fact that many of these parcels are still using outdated practices.
One of these examples includes the use of handwritten Packing Slips that contain SKUs, Delivery addresses, weights, dimensions as documentation between the sender, receiver and all delivery companies between them. Many workers have to be deployed to do the sorting of parcels which more often than not becomes the bottleneck to scale.
How do they tackle handwritten pack slips?
With the rise of Artificial Intelligence and Improvements in Optical character recognition (OCR) systems, many of these companies are looking to find ways of picking up the handwritten text on these pack slips that can send information back to databases in a matter of seconds as soon as they change hands at their warehouses.
These companies figured that by automating these manual processes that could not be done ten years ago, they would be able to reduce delivery costs and increase transparency when data points are captured from these handwritten pack slips that were previously only found on the delivery boxes and not tracked in online systems.
Taking these large number of images with boxes with their corresponding data points, they are passed to the deep learning classification models that are able to train and pick up key data points like addresses, packing slip Identification number and SKUs for the millions of boxes passing through the warehouse or consolidation point using their newly built AI scanners.
Most importantly, the technology will continue to improve and these outdated processes would soon be overcome, benefiting consumers like every one of us.
By Lee Jin
Co-Founder & COO, Tictag