Inefficient Logistics Planning Systems are Hindering Progress

The e-commerce industry has experienced remarkable growth, bringing about a significant transformation in the global marketplace. As digital marketplaces continue to expand, the expectations and demands of consumers are shifting. Today, customers are seeking cost-effective solutions coupled with swift delivery options. Consequently, improving last-mile delivery has become a critical prerequisite for building and maintaining customer loyalty in online retail.

However, last-mile delivery services come with their own set of challenges and hurdles. According to a report by SOTI Inc., over 61% of logistics companies agree that last-mile delivery is the most inefficient process within the entire supply chain. One primary challenge affecting last-mile delivery is the use of outdated technology. The report reveals that nearly half of global transportation and logistics companies still rely on obsolete technology for their last-mile delivery operations.

Outdated technology poses limitations in combating delays and high shipping costs. Current processes often depend on unreliable data sources and obsolete IT systems, resulting in limited coordination across functions. This can lead to inefficiencies and hinder operational performance.

Fortunately, artificial intelligence (AI) and machine learning have the potential to dramatically improve supply chain performance, especially for consumer-packaged goods (CPG) companies. A promising approach for CPG companies is integrating their entire end-to-end supply chain, enabling real-time, autonomous planning of most processes and decisions.

In addition to outdated technology, other challenges in the last-mile delivery process include a lack of transparency, late deliveries, inefficient route planning, poor granular data tracking, and more. The last-mile problem encompasses these typical inefficiencies and factors such as short delivery timeframes, same-day delivery expectations, fuel costs, last-minute route changes, failed deliveries, and rising customer expectations.

The last mile of delivery is often the most expensive and time-consuming part of the shipping process, accounting for approximately 53% of total shipment costs. Traffic congestion poses another significant challenge as delivery vehicles navigate through crowded streets and highways, resulting in delays and increased delivery times.

Various approaches have been suggested, with technology, especially automation, proving to reduce time, resources, and expenses for companies effectively. A study quoted by Salesforce indicates that automation can help employees save between 10% and 50% of the time previously spent on manual tasks.

Last Mile Delivery Software, or final mile delivery software, offers a comprehensive solution for businesses to monitor and complete shipments from warehouses, stores, or distribution centers to their final destinations. These software products can effectively manage, schedule, and track real-time deliveries. Examples of Last Mile Delivery Software include Onro, LogiNext Mile, Tookan, Wise Systems, HERE Technologies, Deliforce Delivery Management Software, Dispatch Science, Locus Dispatch Management Platform, and DispatchTrack.

AI can significantly contribute to optimizing the last-mile delivery process, predicting demand patterns, enhancing delivery routes, and improving communication between delivery drivers and customers. AI is crucial in selecting the most optimal carrier based on a balance of operational factors and associated costs. By running algorithms across available carriers, a decision can be made to choose the most cost-effective option. Moreover, AI can provide tools with greater visibility and insights into the complex last-mile delivery process. By leveraging AI, humans can perform their tasks better, handle higher volumes, and achieve a better work-life balance.

Several companies have already embraced AI in their last-mile delivery operations. For instance, a grocery retailer, Tesco collaborated with Satalia, an AI consultancy in London, to develop a last-mile delivery system from scratch. This innovative system compares the order location and basket size with all other scheduled orders, providing a verdict on feasibility and available slots in less than half a second.

Another notable example is Bringg, an AI-driven delivery orchestration platform utilized by major retailers, including Walmart, McDonald’s, KFC, and METRO. Bringg’s platform primarily caters to retailers, restaurants, and grocery stores, offering advanced capabilities for optimizing last-mile delivery operations.

In conclusion, the inefficiencies caused by outdated logistics planning systems are hindering the overall efficiency of last-mile delivery. To address these challenges and enhance supply chain performance, companies must invest in modern technology, with AI and machine learning playing a pivotal role. AI empowers businesses to predict demand accurately, optimize delivery routes, and improve customer communication. With AI, companies can anticipate customer needs, plan efficient routes, and provide better support, enhancing overall performance and customer satisfaction. Automating and adopting last-mile delivery software can streamline operations, saving time, resources, and costs. Companies such as Tesco and Bringg are already harnessing the power of AI to transform their last-mile delivery processes. Businesses must embrace AI-driven solutions to optimize operations, enhance customer experience, and adapt to evolving market demands to stay competitive in the dynamic e-commerce landscape. By doing so, businesses can improve the efficiency and effectiveness of their last-mile delivery operations, meeting customers’ evolving demands and expectations in the digital era.

Conclusion:

According to FORBES, – “Logistics Study Reveals Three Potential Cures To Global Supply Chain Problems,” this year has witnessed a significant increase in supply disruptions among shippers, with 83% reporting such disruptions. This figure represents a notable rise from the 49% reported in the 2021 survey. In response to this, an equal proportion of shippers (83%) expressed their intention to modify their sources of supply. The aim is to rebalance their reliance on regional and local/domestic sources, thereby reducing vulnerability to global disruptions.

The study also revealed that 68% of respondents believe supply chains have become excessively globalized. Furthermore, 45% of the surveyed companies anticipate adjusting their production locations within the next three years. These adjustments are expected to be crucial in minimizing the far-reaching consequences of a single breakdown in the global supply chain. Localisation of sourcing and efficient planning will ensure seamless flow of goods and information within logistics network.