Innovation in Logistics: Redefining the world of logistics

No industry is immune to disruption. While some are actively finding ways to innovate and disrupt how things are being done traditionally. Logistics is one such industry that has been there since many decades and sits at the tipping point of disruption. In this comprehensive blog we will be diving deeper into how companies like FarEye are redefining the mammoth of an industry that is Logistics and supply chain.

1. What is logistics and why is it important
   Logistics is widely considered the salient hero behind the smooth functioning of the world. From facilitating our day to day retail deliveries, to ensuring the supply of critical medicines to the needy. Logistics form the backbone of global commerce.

2. The changing ecosystem of logistics
   Logistics is a highly dynamic and ever-changing industry that is the first to be impacted by moving global macro and micro factors alike. Many trends have shaped the industry in the last couple of decades. Factors such as emerging technologies like AI, rise of environmentally conscious consumers and the big-bang like explosion of ecommerce with the likes of Amazon and retailers have all shaped how goods and services are reaching the consumers.

3. What we are going to cover in the blog:
   The blog will cover two primary areas, (a) innovation in logistics and (b) role of tech innovators in the field of logistics like FarEye. We will be going deeper into some of the emerging technologies as well as the tailwind effects of such innovation in the grand design of the supply chain.

Logistics has always been a paper and process heavy industry with a lot of moving parts including but not limited to the thousands of delivery champions on road, countless paper documents required for movement of goods across borders, vehicle/fleet management and more. The move to the digital front was a long time in coming and has arrived in its full glory with the first step towards digitizing followed by automating and autonomization.

1. Digitization and data-first approach to optimization

More and more traditional players in logistics are aggressively leaning heavily on technology to carry out basic operations that were once paper-heavy. With digitisation the industry opened to new facets of optimization using real-time analytics, internet of things (IoT) and predictive analytics. The data first approach allows these players to optimize parts of their operations that were once hidden behind the stacks of paper-based processes. While these technologies do open up areas for companies to track, measure and improve their processes it also opened the industry to a potential new challenge.

Challenge: With all the data that is being generated and captured the concern of consumer data privacy and security started becoming a real threat.

Ensuring that all sensitive information is protected from the growing threats of the digital age is the first and foremost challenge to overcome for anyone looking to get their business into the digital age. While the benefits of digitisation are substantially more, the cost of successfully implementing the same includes not only significant capital expenditure but also significant change management.

2. Automation and Robotics

One of the major metrics for logistics companies is to reduce the time a delivery spends within the walls of the warehouse. Global leaders are employing automation and robotics to enhance their warehouse and in-wall operations. Using such tools and processes there is a scope to fine-tune every inch of warehouse space and time to dispatch. The use of AGV or Automated guided vehicles within the warehouses are reducing errors in shipment handling and reducing exceptions at a scale higher than ever seen before.

Challenge: With deep rooted automation practices and employment of autonomous robots for daily chore-like works opens up the threat of job displacement. Logistics companies must be able to strike the balance between automation and keeping a motivated skilled workforce. Moreover, with heavy reliance on automation, companies should always have a backup plan in case of technical failure such that the manual team can pick up the work without impacting the day to day operations while the tech is brought back up.

3. Artificial Intelligence (AI) and Machine Learning (ML)

AI has been slowly taking over how we operate the supply chain especially in fields like route optimisation, exception prediction and forecasting. This has a direct impact on reduction of wastage and wasted delivery attempts. With the likes of GPT/Bard and other LLM models there is a huge opportunity for improving the long lasting issue of address parsing and geocoding. Moreover, AI and ML technologies are enabling predictive analytics that are able to predict and forecast both orders and exceptions thus having a direct impact on the delivery attempts and fraud detection

Challenge: AI/ML have a lot of potential in terms of optimization and productivity. Onboarding and integrating AI/ML technologies require large-scale data pipelines and skilled professionals. Further the challenges of AI/ML are still being explored and AI-governance is also becoming a serious research topic.

4. Innovation in Last Mile Delivery

Last Mile deliveries contribute to over two-thirds of the total delivery cost. The opportunity for optimisation is higher than any other part of the delivery process. With the surge of demand for online deliveries the impact of technology is higher than ever. Companies are testing drone deliveries, automated delivery vehicles and robots, smart pickup and drop parcel lockers and integrated omni-channel delivery channels. Consumers are more cost conscious than they have been when it comes to deliveries and last-mile. While consumers are ordering more the appetite for delivery cost is at its all time low

Challenge: While drones and other automated delivery options have the potential of reduction in cost and time they post another threat of UAV traffic and integration of such modes with traditional modes of consumer. With the increased adoption of AI the rising need for AI-governance is taking over. The concerns around AI is also a legitimate challenge that companies looking to integrate AI needs to look at before an extended release of this technology.

5. Sustainability and green supply chains

The need for saving our planet is more real than it was a few years ago. What was once a regulatory requirement is a critical aspect to ensuring we are moving towards a sustainable future. Companies are moving towards adopting electronic vehicles and using alternative fuel and power sources. Packaging is another area where companies are innovating the use of recyclable materials. Such sustainable options not only are moving the logistics industry to a more sustainably conscious industry but also appealing to the more informed and aware customers. With over one-third retail customers willing to opt for sustainable deliveries at the expense of speed and cost

Challenge: Sustainability is still a high cost initiative. EV and alternative fuels are still a topic for research and companies are working towards reducing the cost of moving to these options but we are still further from the ideal solution for mass adoption. Even though there are regulatory bodies for sustainability initiatives a lot of regions are still to take this with the same seriousness as the more developed economies.

6. Blockchain for Supply Chain Transparency

Blockchain or more technically known as DLT (distributed ledger technology) provides a way for recording and managing transactional information which is immutable and completely traceable. Blockchain has a very real application to the supply chain where data flow is critical. Companies are experimenting with DLTs and blockchain for maintaining and transacting shipment records where authenticity and integrity of data is of utmost importance

Challenge: While blockchain and similar technologies have the potential to introduce a lot of transparency the technology is not ready for real-time like systems. The technology is still being worked on in terms of its speed and throughout. The fastest blockchains are still 10x slower than the closest traditional alternatives.

7. Move to accurate predictive forecasting

Demand forecasting has been one of the most researched topics in data analytics and prediction. Specifically for the supply chain industry where being prepared for a surge in demand is what differentiates a profitable logistics operation from a bottom-line draining operation. By analyzing historical data ML models are able to predict with high accuracy the potential increase or decrease in demand of deliveries. This coupled with established sales and manufacturing forecasting models are leading to much more efficient vehicle and fleet management practices

Challenge: As with any other ML based innovation forecasting requires substantial investment in both data pipelines and qualitative understanding of the macroeconomic environment. Coupled with lack of highly skilled ML professionals this is a challenge for mass adoption and development in-house. This is where companies like FarEye step in.

8. Internet of Things (IoT) for Asset Tracking

Internet of things is an established and well adopted technology and has seen high adoption specifically for asset tracking and long-haul trucking. Even within larger premises or warehouses IoT is being adopted for tracking of movement of goods within the larger area. This coupled with geofencing technology where entry and exit of assets can be tracked. There is a strong use case for temperature sensitive goods with the detailed level of tracking IoT brings to the fray

Challenge: Cybersecurity is the biggest threat to IoT based deployments. Thus protection of these devices/systems against such threats is the biggest challenge. Even though the globe is moving towards a higher quality internet connectivity, IoT is still heavily dependent on network connectivity.

9. Autonomous Vehicles for Long-Haul Transport

Self-driving vehicles are being tested across different geographies with varying success. However, by reducing the reliance on drivers for long distance trips companies are bringing in optimisation at a whole different scale. This has the potential to disrupt the industry at an unprecedented level

Challenge: Autonomous vehicles while promising a much higher scale of optimisation there are significant regulatory and geographical challenges with the adoption of such technologies. Both from a job displacement and front he security and safety perspective of other vehicles sharing the road.

10. 5G connectivity and Edge computing

The average speed and connectivity across the globe is going through a massive upward shift. With the launch of 5G across the globe high speed internet is becoming commoditized and is lying in the hands of the end consumer. With this availability of high speed internet and faster computational resources companies are able to leverage on more data-heavy products such as large-scale AI models.

Challenges: Though the technology is being rolled out across the globe its adoption and availability across tier2 and tier3 regions is yet to be realized.

11. Warehouse operations enhancement using Augmented Reality (AR)

AR is being tested and used within warehouses with devices such as smart glasses, visual aids and AR supported loading devices. The use of AR is a game changer when it comes to integrating optimization to the real world. This has a positive impact on training times, improves accuracy for order picking and overall efficiency in warehouses.

Challenges: Change management and requirement of devices capable of handling AR is the deterrent in widespread adoption of the technology.

12. Data-first supply chain

Logistics industry generates more data than any other industry ranging from order data to delivery critical data. With the large amount of data being generated there is a huge opportunity in handling and managing that data to turn it into insights. Effectively utilizing the data and turning it into insights open up hidden opportunities in the supply chain processes.

Challenges: While generating huge amounts of data holds a large opportunity of insights it also brings the challenge of security and processing this scale of big-data. This requires substantial investment into data capabilities and a dedicated team of data scientists to manage and improve the quality of insights.

13. Ecommerce Integrations

There has been a constant upward trend in ecommerce orders with more familiarity of customers and trust with buying online. With this trend a lot of direct to consumer brands are opening up their onlines stores using a mix of platforms like Shopify. This upsurge requires logistics companies to be able to accept and manage orders for these customers directly from their ecommerce stores. With advanced tech companies are able to onboard such partners on day one and start shipping.

Challenges: Although this is a quick fix in terms of aligning stores to a potential carrier. This requires a certain level of technical maturity with both the carrier and ecommerce store.

FarEye at the forefront of innovation

FarEye is a leader in logistics technology and has been creating pioneering products with the use of AI to not only aid companies in optimizing their logistics but enabling them to make logistics profitable.

FarEye is empowering our partners to adopt and drive disruption

FarEye has been partnering with companies that are looking to embrace disruption and take logistics to a whole next level. FarEye, having partnered with logistics leaders like DHL and Blue Dart, have revamped the meaning of profitable and optimized logistics operations.

Shaping the next decade of logistics

The next decade is expected to be shaped by sustainability, AI, a more human-involved supply chain and a safety-first working environment.

Emerging technologies and their impact

The technologies we covered in this article have the potential to completely upgrade the way we look at logistics. We see the next decade to have considerable shifts in our way of doing things with the aid of these and more.

A Human-first approach to supply chain management

Even though AI and autonomous technologies possess the risk of job displacement. The requirement of a skilled workforce is only going to increase. We see the role of humans shifting from more menial chores like tasks like racking, labeling to more knowledge work like routing and planning.

1. What is the significance of digitalization in logistics?

Answer: Digitalization in logistics is the process of integrating technology and data-driven solutions to optimize supply chain operations. It enhances efficiency, bolsters visibility, and empowers data-driven decision-making across the entirety of the supply chain.

2. How do sustainability initiatives impact the logistics industry?

Answer: Sustainability initiatives in logistics involve reducing carbon emissions, adopting eco-friendly packaging, and using alternative fuels. These measures not only align with environmental goals but also appeal to environmentally conscious consumers and reduce long-term operational costs.

3. What challenges does the logistics industry face with autonomous vehicles?

Answer: Challenges related to autonomous vehicles include regulatory hurdles, ensuring safety on public roads, and addressing concerns about job displacement in the trucking industry. Conquering these challenges is imperative for achieving widespread adoption of autonomous technology.

4. How does blockchain enhance supply chain transparency?

Answer: Blockchain technology creates an immutable and transparent ledger that records transactions throughout the supply chain. This transparency ensures the integrity of data, making it difficult for anyone to alter or tamper with records. Consumers can trace a product's journey, enhancing transparency and trust.

5. What are the key challenges logistics companies face in adopting sustainability practices?

Answer: Challenges in adopting sustainability practices include the high upfront cost of transitioning to eco-friendly technologies, concerns about profitability, and the need for regulatory compliance. Companies must carefully balance sustainability with their bottom line and navigate the regulatory landscape to succeed.