Real-time Transportation Visibility : Driving Efficiency and Transparency in Global Supply Chains

A decade ago, supply chain had just dipped its toes into the pool of real-time visibility. There were certain technologies to track shipments as thegoods travelled from the manufacturerto the warehouse and then to the retailer and the consumer. Still, they were less efficient than they are today. For instance, the tracking of the goods was minimal and often delayed without notice and time, resulting in a lack of communication at every step of the process.

However, since the Covid-19 pandemic pushed people into isolation and at-home deliverybecame the norm, the importance of supply chain visibility has skyrocketed.Case in point, a recent Verte research found 91% of consumers routinely track their goods. Another study revealed that around 60% of shippers view real-time shipping visibility as essential when choosing a carrier. Can you imagine if you were not getting notifications of your order’s shipping or delivery status?

When you think about your package’s journey, the route of a single productis complex and tracking its location even more so. While this entire process may seem daunting and exhausting, it does not have to be.

With great technology at our disposal, real-time visibility in transportation is becoming easier to achieve. For instance, think about when we used to store our precious memories in disposable film and now,to a point, where our photos magically get saved up in the clouds. Such technology and more also exist in the plane ofsupply chain. With predictive technology that can let you know what to expect to mitigate losses, it is time to integrate such ease in real-time transportation.

Components of Real-Time Transportation Visibility

Let’s take a deep dive into the components of real-time visibility and how it helps enhance consumer experiences:

1. Tracking and monitoring

Although a decade agotracking existed, it was not as sophisticated.Companies relied on legacy technology such as manually updating Excel sheets.

Real-time tracking technologies have progressed and found widespread adoption, including Global Positioning System (GPS) tracking, Radio Frequency Identification(RFID), and telematics systems. These technologies produce real-time location and status data that may be communicated across the supply chain and integrated into transportation management systems (TMS).

We are viewing the perfect blend of these basic formats in high-end systems such as track and trace. This allows you to monitor the movement of goods throughout the supply chain anytime and anywhere. This system makes it easier to improve:

• Customer experience as you can provide real-time updates on their order.
• You will be able to reduce costs by checking the shipment in real-time, and you can take remedial action on any issue that may arise in an already complicated process.
• All these combined increases accuracy as it reduces risks.

2. Communication

The communication that took place between carriers, shippers and customers relied on faxes, emails and phone calls. But now, we have platforms that enhance communication and coordination, such as:

• Collaboration tools: The beauty of instant messaging is that it connects you to people all around the world and has enhanced communication immensely. Everyone involved in your supply chain process can now communicate, swap information and even collaborate on problem-solving, which leads to faster decision-making.
• Dedicated applications: Many applications aid personnel such as drivers, logistics and even consumers to stay connected. Many businesses create personalized applications to provide them with notifications, updates and even messages to ensure no communication disruption.

Now your customers will be able to know when the shipment is delayed because of unforeseen conditions such as heavy rain and snow. This provides transparency to your customers and helps deliver a better customer experience.

So, I, as a consumer, may be perfectly fine with something taking it three, four, or five days to get to my home, right? But if you tell me it’s gonna be there on that fourth day and it doesn’t show up, then I’m gonna take you to task, right? Because there’s no reason in 2023 that you can’t communicate with me.

– Mark Delaney, Vice President , FourKites, Inc.

• Integration with Enterprise Systems: Enterprise resource planning (ERP) and transportation systems communicate more easily. To achieve accurate and current information for all personnel, real-time updates from transportation systems, such as status changes, delivery confirmations, or delays, can instantly synchronize with the central enterprise systems. This helps everyone stay connected even without communicating with each other.
• Digital Documentation

  Similarly, with digital documentation, such as electronic proof of delivery systems (ePod), the administrative burden of using paper documentation is removed, and the information can be passed on more quickly to different parties involved.

3. Data integration

Integrating data from different systems, such as that of transportation services or supplier, allows everyone in your supply chain process to be interwoven with the real-time location of the products. This makes it easier to have a holistic view of real-time transportation activities.

• Data sharing: The rise of data sharing in industry-specific networks and platforms enables supply chain parties to exchange data safely in a standardized manner. These solutions enable the seamless integration of real-time transportation data, enabling stakeholders to see the supply chain as a whole and collaborate on informed decisions.
• Blockchain technology: Blockchain technology has the potential to revolutionize data integration in the supply chain by providing a decentralized and irreversible record for transactions and data sharing. It is crucial to recognize that blockchain technology has only a limited number of real-world applications in this sector.

Although blockchain technology has several advantages, such as improved data integrity and transparency, it has not yet been widely adopted in the supply chain. However, future improvements in supply chain security and efficiency seem hopeful given the continued development of blockchain technology.

As a result of you sharing your visibility data with me, that means that I can provide better service to our mutual end customers that are walking in the store looking for product.

– Mark Delaney, Vice President , FourKites, Inc.

4. Interfaces Integration

Real-time transportation in the supply chain requires integration, which entails the smooth connection and management of numerous systems, procedures, and stakeholders.

• API Integration: Application programming interfaces (APIs) are essential for facilitating automatic system integration. APIs offer standardized interfaces and protocols that enable real-time data exchange and communication across various applications. API integration enables automation, data synchronization, and cooperative activities by facilitating the exchange of information between systems.
• Cloud-based Integration: The ability to store, process, and integrate data on a flexible and scalable platform has revolutionized integration. Cloud integration solutions make seamless communication between on-premises systems, cloud applications, and external partners possible. Real-time data synchronization, increased accessibility, and improved teamwork are all made possible through cloud integration.

Applications of Predictive Analysis in Real-Time Visibility

Companies can use real-time transportation to reduce risks, make data-driven choices, and forecast future trends. This promotes the efficiency of transportation procedures and guarantees the overall effectiveness of the supply chain.

1. Demand forecasting

Businesses may precisely forecast future demand for transport services by using predictive analysis techniques like time series analysis and machine learning algorithms. These predictive models examine historical data, market patterns, and outside variables to provideaccurate forecasts. This enhances capacity planning and resource allocation, enabling organizations to effectively satisfy client expectations.

2. Route Optimization

Another important application of predictive analysis is route optimization. Businesses can use predictive models to find the most cost-effective transportation routes by taking into account factors like traffic patterns, weather, and prior delivery information. As a result, delivery times are shortened, fuel costs are lowered, and operational effectiveness is increased.

3. Supply and Inventory Management

Predictive models look at past data, demand trends, lead times, and other variables to accurately predict future demand. This makes it possible for companies to maintain ideal stock levels, reduce excess inventory, and avoid shortages, all of which increase supply chain effectiveness.

4. Risk Reduction

Real-time transportation enables companies to make data decisions, anticipate future trends and mitigate risks. This helps in optimizing transportation processes and ensuring the success of the overall supply chain performance.

The use of predictive analysis is essential for lowering the risks connected to transportation operations. Predictive models can spot probable bottlenecks or delays in transportation by examining historical data, weather forecasts, traffic patterns, and other relevant information. Businesses should take proactive steps to reduce risks, such as rerouting deliveries or moving forward pickup times, to guarantee on-time delivery and customer satisfaction.

5. Equipment Maintenance

Predictive analysis methods are used in the transportation industry for equipment maintenance. Predictive models can forecast equipment maintenance and failures by tracking the health and performance of transportation assets.

These models can detect probable equipment failures or maintenance needs by examining sensor data, previous maintenance logs, and other elements. As a result, unplanned downtime is reduced, and asset utilization is increased for organizations by scheduling preventive maintenance.

6. Client Satisfaction and Behavior

Predictive models can foresee client preferences, spot future problems, and customize services by examining customer data, feedback, and transaction history. This enables companies to improve customer satisfaction, raise retention rates, and make decisions that are centered on their needs.

What are the Challenges of Predictive Analysis in Real-Time Visibility?

While with the efficiencies of real-time visibility, some challenges may hinder your transportation processes. Consider these challenges as a way to mitigate and work on reducing these problems.

1. Failing to update timesheets timely

The most significant issue with time monitoring for corporations is unquestionably lack of information on the timesheets. You might ask your staff to submit timesheets weekly, biweekly, or monthly, depending on your operations. It usually involves synchronizing the billing cycle.

The usual rule for updating timesheets is that it should occur as soon as an activity is finished, if possible. People frequentlyforget how long a particular task took them, which lowers the accuracy of their records. Additionally, if a lot of workers are tardy with their timesheets, you lose time sending out repeated reminders. This reduces the effectiveness of your supply chain, and more time gets dedicated to updating numbers than concentrating on the business operations.

2. Adapting to real-time reporting

Some traditionalists may not think the difficulties of setting up company-wide software and the ensuing data migrations are worth the effort. Therefore, it will be crucial to mentally prepare staff members with support and training in the new data reporting software.

There are more mindsets to get rid of besides traditional reports. With a traditionalist’s outlook on things and experience with conventional job descriptions, they might be accustomed to relying on static reports and manual data analysis techniques. Without advanced analytics and real-time insights, traditional job descriptions could have concentrated on routine data input and reporting chores.

The sophistication of job descriptions has increased with the development of real-time customer relationship management (CRM) systems and predictive analytics. Traditionalists must broaden their knowledge bases and acclimate to new tools and technology that offer real-time CRM insights. To make this adjustment, one must adopt a new way of thinking about and using data to get deeper customer insights and facilitate more sensible decision-making.

Top of mind with our customers these days is employee satisfaction. Because it’s very expensive to lose a good employee, especially someone who’s been there for a period of time.You invest in all that training and that sort of thing. So, for them to be mired down by spreadsheets and phone calls and text messages and all that. If you can give them that single pane of glass view and you can give them that visibility and the confidence that they’re communicating to their customers, something that’saccurate, right?

– Mark Delaney, Vice President , FourKites, Inc.

3. Volume changes

Real-time data typically does not flow at constant rates or quantities, making forecasting how it could behave difficult. Unlike when managing batch data, it is not practicable to keep restarting the process until a pipeline defect is discovered. Since data is always flowing, handling mistakes can have a cascading influence on the outcomes.

The limitations of real-time data processing phases further complicate standard troubleshooting procedures. Due to this, even while testing might not catch every unexpected fault, more recent testing platforms can better control and minimize problems.

4. Multiple data sources and formats

Sometimes it can take more work to choose what type of data format is perfect for your organization. The variety of data formats and the growing number of data sources may provide challenges for real-time data processing pipelines.

A wide range of Internet of Things (IoT) devices are used in production to collect performance data from different pieces of equipment. All these use cases employ various data collection techniques and frequently use various data formats.

Even though real-time visibility significantly improves transportation procedures, it is crucial to recognize and deal with any potential difficulties.