Shipping Data: How Machine Learning, AI, Automation & Chatbots Create Hyper Efficiency

Robotic process automation (RPA) leverages innovative software tools that can either partially or fully automate human activities to become more efficient and productive. RPA is increasingly adopted within the supply chain to take over mundane and repetitive tasks such as managing shipping data, filing paperwork, answering general FAQs, entering data, reading and responding to emails, and performing other basic tasks. Smart technology based on machine learning and AI chatbots are beneficial for several critical systems and functions within the supply chain. This innovative technology helps managers and team members alike accomplish more. Let’s take a closer look at the problems contributing to their adoption and how these advanced technologies can help.

Why Shippers and Carriers Struggle With Managing Shipping Data

Supply chain technologies are now focusing on logistical planning and shipping data management in order to improve functionality and address issues in real-time. Outdated methods and traditional protocols are no longer effective. This includes email management as well. Trying to meet current market demands with obsolete systems is an exercise in futility, and that is causing many shippers, carriers, and forwarders to struggle. These major areas of the challenge include:

    • Scalability to shift productivity levels and focus on meeting current market trends and consumer demands.
    • Adaptability to grow and expand as needed, to align with customer habits and current market indicators.
    • Transparency within the supply chain to quickly and easily note problem areas and implement fixes.
    • Communication options within the supply chain, with third-party team members, and consumers.
    • Accessibility to data and real-time information to ensure proper monitoring and communication.

 

  • Networking solutions that improve the overall functionality and productivity of transportation systems.

 

Overcoming these common problem areas can help shippers and carriers maintain a competitive edge in today’s volatile market.

Advanced Tech Promotes Efficient Collaborations and Mutually Beneficial Partnerships

AI, machines, and other advanced technologies surrounding logistics automation can help elevate the customer experience, improve efficiency, and enhance collaborations for shippers and carriers. According to Supply Chain Digital, at the heart of any effective partnership is the need for real-time, accurate, and accessible shipping data. Establishing and maintaining mutually beneficial partnerships remains a critical component to current supply chain operations. The driving force behind many shipping and logistical changes in recent years is the continual need for growth and adaptability. No one company can meet all consumer and industry needs, so collaborations and partnerships are becoming the norm. 

AI’s ability to collect meaningful, accurate data throughout the supply chain drives the continuous improvement of many essential functions within network partnerships. Possible applications can be deployed to capture information from emails, upload that information to relevant systems, and apply it in simulated chats with customers. 

Machine learning within the supply chain network is also vital for effective planning in customer interactions, shipping data collection and analysis, innovative data distribution, real-time processing and communications, and more. Utilizing the advancements that have been made in these tools and software continue to drive the market and allow transportation and logistics managers to process shipments more effectively. 

Other Ways Chatbots and Automation and RPA Help Companies Get More Done

Access to real-time, accurate shipping data and implementing automated analytics are critical for informed decision-making and accomplishing more. There are three main sectors of analytics that can impact RPA implementation within the supply chain, including:

  • Descriptive analytics gives shipping and logistics managers hindsight into past performances and trends to help identify what changes may be needed or why a customer experience fell short.
  • Predictive analytics addresses what may occur soon if specific actions or decisions remain unaltered in current systems or current interactions, such as a greater risk for a return due to poor customer engagement.
  • Prescriptive analytics provides supply chain managers with recommendations based on past data analytics and current trends, such as when to send updates to customers and alternate solutions to current problems. 

Coupled with advanced robotic chatbots, automation and analytics can help companies drive growth and scalability in today’s volatile market by automating additional back-office processes. Remember that includes email response bots as well. 

Capitalize on the Power of RPA to Improve End to End Performance and Outcomes with Enhanced Shipping Data Access and Utilization

The next evolution of the digital supply chain is coming fast. The sudden push toward automation and more innovative processes continues to impact shippers and carriers alike. This shift has been primarily due to the drastic changes seen within the supply chain network in recent years. This trend is in no way slowing down, and shippers and carriers that want to remain relevant in the market must capitalize on the power of RPA and improve performance and outcomes throughout the entire supply chain network.  Book a demo with RPA Labs to see our chatbots in action.

Share This Post

Share on facebook
Share on linkedin
Share on twitter
Share on email

More To Explore