Six Key Benefits of Automating Core Logistics Operations

Get back into your millennial shoes (or pajama; whatever still fits). Imagine yourself relishing piping hot coffee on your porch when a faint whirring sound distracts you. A flying object carrying a tiny box descends, leaving it right in front of you. How would you have reacted?

Even today, such “sightings” are still not commonplace. But what’s different now is your second thought about this situation. Technology has made it possible (if not normalized) for us to imagine and even live in a world of AI-driven drone deliveries. Advanced GPS systems and environmental data enable driverless vehicles to plot out more efficiently than human drivers. Driverless vehicle waiting outside homes to deliver parcels is the reality for some in the US, Saudi Arabia, and other parts of the world. Such is the precision with which artificial intelligence works. So today, you’d respond to “Why me?” with a “because the parcel probably has my name and address, or the drone has access to data on real-time location.”

The Future in Motion: Automation is Revolutionizing Logistics

Automating core logistics processes has opened up a gamut of possibilities. It is optimizing processes to save costs, reduce investments in person-hours, shrink carbon emissions, optimize KPI management, and much more. Let’s glance through some of the major advantages of logistics automation.

1. Intelligently Assigns Sustainable Delivery Modes Through Auto Allocation 

Auto allocation of vehicles is the most compelling use case of this potent combination of AI and Machine Learning technologies. It eliminates guesswork and human dependencies to consider various pre-fed parameters to intelligently assign vehicles. The decisions are faster, more efficient, data-driven, and less prone to errors than manual ones. Delivery managers use the technology to prioritize eco-friendly modes of transportation to execute nearby deliveries. The system considers delivery restrictions, such as order weight, dimensions, volume, radius, etc., to automatically choose electric vehicles, bicycles, autonomous vehicles, drones, and other sustainable modes of transportation for deliveries. It applies the same logic for delivery to other zones and territories that may be farther away. 

2. Reduces Carbon Footprint Through Route Optimization

Logistics chains aren’t that eco-friendly. They cause more than 80% of carbon emissions globally. Since supply chain and logistics are inextricably linked, and businesses cannot wholly halt either, it is wise to devise ways to reduce the carbon footprint on the go. For instance, shipping goods people will not use/buy is bad for businesses and the environment. Also, the logistical activities will release CO2 emissions for nothing. But gauging what is unlikely to be purchased and what may see more demand is difficult when done using traditional methods.

Thankfully, AI-based intelligent systems can accurately predict demand for products. Making use of predictive analytics, companies can only ship products that shoppers are going to buy. A leading Swedish fashion brand uses AI to predict and analyze fashion trends and adjusts shipping orders accordingly. It has helped the company to reduce waste and make more sustainable decisions.

Additionally, AI-powered logistics management solutions can wisely plan logistics routes to cover multiple touchpoints and avert delays due to traffic jams and roadblocks. They reduce the distance traveled by 5%, curb vehicle idling, shrink trip volumes by 6%, and eliminate empty miles to minimize fuel consumption and carbon emissions. For the world’s most-loved pizza chain, the technology has reduced the average distance traveled by bikers by 23%. Advanced sustainability dashboards allow shippers/businesses to track carbon emissions across ocean and air freight even before the shipment journey commences. 

3. Ensures Costs Savings

Unprecedented fuel price hikes, inefficient processes, delivery reattempts, etc., make logistics a costly affair. Close to 53% of the total shipping costs are incurred in the last mile, making it the most inefficient logistical leg. Businesses manually grappling with this mammoth task are highly susceptible to losing the fight and bidding goodbye to profits. 

AI helps businesses bolster their logistics operations from sudden cost surges. As mentioned above, AI and ML-driven route optimization and planning engines plan effective routes to the customer location, which minimize the risk of route deviation for drivers. It lowers last-mile delivery costs by 14%. 

One of the significant causes of delivery reattempts is customer unavailability at the time of delivery. Dynamic routers engage end customers by communicating delivery details to them. A message containing a tracking link helps consumer track delivery progress in real-time. The system also arrests delivery deviations by raising an alert if driver location and actual delivery locations do not sync to curb fake delivery attempts due to mock GPS locations. It also tracks whether the driver has followed the system-suggested planned route.

To find out how automation makes quick commerce operations economically viable, click here.

For CEP providers, geocoding helps convert poor-quality addresses into precise coordinates, leading drivers to the exact delivery location. This increases the first-attempt delivery rate, lowering reattempts. According to McKinsey, the successful implementation of AI has helped businesses reduce 15% in logistics costs.

4. Increases Vehicle Productivity Through Capacity Utilization

What’s better than optimizing the efficiency of existing vehicles and delivery drivers? It is projected that AI will increase logistics productivity by more than 40% by 2035. Imagine a scenario where a delivery van runs on one-third of its actual capacity. 

AI-powered logistics management tools accurately gauge the optimum levels of vehicles to operate. They consider various vehicle and order-specific parameters such as vehicle type, make, capacity and order weight, dimension, delivery distance, etc., to automatically map orders with the right fleet. It increases vehicle utilization by 31%. It applies the same logic but a different set of parameters for drivers to increase their productivity on the fly. Combined with effective routing and en-route order clubbing, the system increases deliveries per driver by 14%.

5. Enables Efficient Warehouse Operations Through Automation 

Warehouse automation robots use complex algorithms to intelligently pick, stack, and store goods in the warehouse based on their frequency of purchase, ease of access, expiration date, and other factors. So, when the need arises, instead of moving all pallets like some giant Tetris game to find the correct order, smart placement enables a better response. eCommerce and retail giants across the globe, like Coca-Cola, Zappos, Alibaba, and Amazon, use warehouse automation robots to drive greater efficiencies.

6. Improves Logistical Planning Through Predictive Intelligence

Understanding exceptions, emergencies, and risks at the logistics planning stage can make a difference. For example, predictive pickup ETAs for containers can help businesses plan their trucking operations better and improve the utilization of their resources. Providing advanced visibility over shipment movement reduces incidental costs by 34% and enhances customer satisfaction by 64%. According to Supply Chain Dive, 76% of supply chain professionals now use predictive intelligence.

With the great strides of developments in AI and associated technologies, we are likely to see the logistics and supply chain operations become more resilient, agile, and sustainable soon.