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The automatic route planning and optimization software market is expected to expand at a CAGR of 10.9% from 2021 to 2026. And it is no surprise since customers are increasingly looking for faster and free deliveries. This has pushed logistics providers to streamline their supply chains to meet the changing consumer expectations as well as business targets.
Traditional route planning has become too slow for the fast-evolving digital order placement capabilities and multiple variables affecting modern-day supply chains.
Many businesses are actively looking for answers to pertinent questions like
This makes it clear that to deliver on the promise of on-time and cost-effective deliveries, route planning is the key, and the task of selecting optimal routes for quick delivery by the delivery managers is made easier with automatic route planning software. This helps smoothen the process.
In this blog, we will explore the challenges, significance, and benefits that automatic route planning brings.
Automatic route planning for the logistics and distribution sector refers to the process which optimizes delivery operations by creating the most efficient route for quicker deliveries in a cost-effective manner. The routes are planned and optimized on the basis of in-built AI routines that consider multiple optimization criteria, such as area codes, vehicle make, delivery windows, etc.
The route calculation is also based on traffic updates, schedules of drivers, and vehicle size. It is crucial for businesses as it ensures low operational costs, timely route deliveries with real-time information, minimal delays, and higher levels of customer satisfaction. With AI and ML algorithms, route planning software can effectively handle all movements across the first-mile, mid-mile, and last-mile deliveries
Businesses involved in the logistics sector can experience various ups and downs when making multiple deliveries and catering to changing customer demands. Here are a few of the major route planning challenges that businesses face in an increasingly competitive market.
Manually allocating tasks like selecting the right vehicles along with riders, tracking shipments, and designing routes fail to account for critical performance figures concerning business growth. It is difficult to generate reports that managers can use to evaluate business operations in terms of performance and costs.
Key metrics such as the percentage of on-time deliveries, number of orders, miles per drop or cost per drop, and customer retention rate become difficult to determine with manual route planning setup.
A well-planned delivery window is needed for logistics managers to plan and ensure the delivery of goods to consumers within the agreed-upon service terms. However, for businesses dealing with last-mile logistics, planning a multi-fleet distribution operation with traditional route planning ends up being an uphill task.
Further, a lack of real-time awareness can lead to longer routes, resulting in delayed deliveries.
Traditional route planning fails to offer timely, cost-effective, and secure deliveries. And, on customer demand, real-time estimated time of arrival is difficult to come by. This lack of predictive visibility, coupled with inefficient delivery operations, leads to higher delivery costs.
Multiple trips, the additional distance to cover, inefficient returns management and more lead to an increase in delivery cost in the absence of an automatic route planning system.
In the absence of real-time visibility, businesses face difficulties across multiple fronts. Riders tend to deviate from the optimal route, deliveries are mismanaged, customer expectations are not met, and many more lacunes in the delivery process combine to bloat up the overall operation costs.
With smart route planning, logistics providers, businesses as well as customers can check the movement of packages seamlessly. For the service providers as well as businesses, this real-time access to data and information allows effective tracking and monitoring of the fleet.
Traffic congestion, roadblocks, and accidents make the process of route planning and deliveries difficult to plan optimally. Riders have to reroute from the planned route in case any obstructions are there. This increases the time and distance required to fulfill the delivery.
Similarly, for the increasingly popular choice of same-day delivery and hyperlocal delivery, frequent rider trips and the resulting fuel consumption is a huge challenge. Any unplanned or unaccounted increase in time and distance traveled directly increases the operational costs involving the fleet.
In today’s time, customers are eager to track the progress of their orders actively. Traditional route planning fails to provide an estimated time of arrival or current location of the package with pinpoint accuracy. It fails to update the customer in case some unavoidable delay occurs.
This negatively affects the CX associated with the brand. On top of that, due to the inflexibility of meeting changing customer requirements with regard to choice of delivery time and place, the traditional route planning system is fast disappearing from businesses.
With factors such as customer availability, optimization of routes, traffic, and weather conditions, there is significant idle time for riders. It decreases the productivity of the businesses as a whole, as improper scheduling leads to hurdles in the delivery network.
Allotting delivery routes to riders manually not only increases the chances of multiple riders traveling along the same route but also is a key factor behind the morale of the workforce. Moreover, manual route planning fails to optimize the utilization of fleet and rider due to the unavailability of complete and updated information.
Without proper utilization of vehicle carrying capacity, which leads to a higher number of vehicles on the road, manual route planning is a cause for unnecessary fuel usage and results in CO2 emissions. Unlike an automated route planning system, traditional ones fail to provide optimized route plans, accurate distance traveled, and exact fuel expenditure.
This makes it difficult to measure the environmental impact of logistics operations. Moreover, if the emission limits are not entered as a parameter in the route planning software, then it is unmonitored, thus negatively affecting the sustainability goals.
On-time In-full refers to the extent to which shipments are delivered to the accurate destination in terms of both quantity and schedule. The increased burden of last-minute deliveries has resulted in a shrinking of the total delivery time available.
This, in turn, has led to lesser on-time in-full deliveries. Further, there can be multiple SLAs that are not met because of manual route planning.
So, with a manual route planning system, the pressure on delivery performance increases drastically as delivery time frames continue to grow short.
Most businesses allocate route planning duties to a few employees, like route planners and delivery managers, who are familiar with customer requirements and specific delivery locations.
The major problem with this arrangement is that when they leave, the expertise and knowledge need to be rebuilt. This forces businesses to spend valuable time and resources to start from scratch. To avoid this risk, it is critical to use a smart admin tool to store and transfer all of this critical data.
The table below shows the difference between traditional and automatic route planning.
Automatic route planning enables transportation and logistics firms to easily organize routes for multiple drivers. Identifying the quickest and most cost-effective routes can improve the company’s productivity and operational excellence. Below are some significant points that list how automatic route planning has made a difference in the supply chain and logistics:
Route planning makes use of disruptive technologies to automate and provide real-time visibility to logistics operations. This information is used by advanced algorithms to create optimized routes and schedule accurate arrival times.
Alongside this, automatic route planning interprets historical data to make intelligent predictions about repeated congestion trends in order to better predict traffic jams on a specific route.
Automation relieves the workforce of routine and time-consuming tasks. The resources saved, like time and energy, can be better utilized to complete other tasks efficiently for businesses.
Smart route planner assigns loads among available resources automatically and without any unintentional human errors. This helps organize routes logically to accomplish the maximum possible deliveries in the least amount of time.
Many enterprises have resource constraints in terms of the amount of capacity that each vehicle in the fleet can carry. It is critical for order fulfillment to have visibility over resource capacity, including both drivers and vehicles.
Underutilized capacity raises the cost-per-unit associated with the vehicle, and over-utilization leads to burnout. Both of the conditions are troubling and inefficient, keeping in mind the rising demand for same-day shipments.
When an order is received, the smart route planner quickly evaluates the existing fleet’s capability and automatically allocates the resource for fulfilling the order. When an order needs to be assigned to a driver on the road, the route planner assigns it to the nearest agent with available capacity. This helps to reduce delays in deliveries due to knowledge gaps while at the same time utilizing the vehicle capacity to optimum levels for higher returns.
Automatic route planning provides real-time visibility into the fleet, allowing businesses to devise ways to increase productivity while reducing unnecessary miles traveled. This cuts down on fuel consumption. As a result, it also saves money.
Furthermore, it enables small-sized fleets to maximize their routing capabilities within the constraints of their vehicle capacity. It allows them to improve their operations without incurring additional costs.
With the growth of e-commerce, there is an increasing need for technologies that allow the management of numerous deliveries with multiple stops across locations. However, several hurdles, including traffic, tonnage, and no-entry windows, negatively affect the speed of deliveries.
A smart route planning software, driven by machine learning, helps suggests the most efficient and cost-friendly route with numerous stops based on historical data as well as current parameters.
Logistics and transportation companies can improve their delivery service by using dynamic route planning. It enables them to reroute in unexpected situations such as roadblocks, traffic jams, and so on.
It is simpler to add or remove addresses, which would otherwise be time-consuming to manage manually. All re-routing updates are automatically displayed on the driver’s designated screen, allowing for faster navigation and a safer driving experience.
An automatic route planning tool allocates tasks without human intervention, which results in greater fleet optimization. The shipments are allocated in such a manner to ensure maximum work in minimal time, with no errors.
This reduces the need for planning to cater to last-mile deliveries and significantly decreases unnecessary miles per driver through the use of algorithms.
Drivers are notified of schedule changes in real time with automatic route planning. It enables companies to analyze unexpected circumstances such as traffic congestion, road accidents, and so on. Businesses can engage in dynamic rerouting and make decisions quickly with advanced route planning.
Furthermore, all scheduling processes are managed by the software. This allows customers to track their orders on a real-time basis and be informed of accurate ETAs via messages, emails, or calls.
Businesses can deliver at the right address within narrow time windows, meeting the expectations of the customer because route planners use geocoding to pin the specified location.
Furthermore, real-time tracking links are shared with customers via email, WhatsApp, or SMS, allowing them to check the delivery status of their package in real time.
Shipsy’s intelligent automatic route planning and optimization software seamlessly manages fleets for efficient deliveries. The user-friendly software from Shipsy ensures integrations across logistics systems, helps make last-mile operations efficient and provides complete visibility to all customers.
Our AI-powered logistics management platform helps ensure timely deliveries for optimizing capacity utilization. Streamline capturing leased or self-owned vehicle-related data from your ERP with smooth integration. Ensuring transparent last-mile operation with digitized/electronic proof of delivery becomes hassle-free.
Shipsy is transforming the logistics ecosystems to provide outstanding service across industries. The customizable SaaS-based software empowers businesses to gain the following benefits:
Connect with our experts today and request a customized demo to stay ahead of the competitors at every step.
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