Predictive shipping analytics derived from freight data add value and enable more streamlined logistics. This leads to the natural benefit of tracking a shipment’s estimated time of arrival (ETA) and helping your team stay informed and responsive. Companies that can provide reliable tracking services, accurate estimated times of arrival, and real-time shipment status and location become go-to brands.
1. Use Shipping Analytics for Continuous Improvement
2. Increased Visibility Reduces Confusion Over ETAs
Visibility remains a priority for supply chain managers, and with peak season quickly approaching, is the one thing needed to increase traceability and predictability of shipment ETAs. There are many ways to achieve this goal, ranging from blockchain applications to instant notifications. In other words, using a system that provides instant notification, exception automation, and real-time shipment status becomes even more crucial. Using predictive shipping analytics, supply chain parties can identify when to reorder stock, account for carrier capacity constraints, plan unloading and loading schedules, and more. At the same time, integrated systems are critical in keeping everyone on the same page, including shipper-carrier points of contact. The sum of the data helps to improve overarching expectations for capacity needs while also helping your team understand what’s happening and why.
Here’s another point of interest relating to replenishment and the need to manage risks to maintain inventory: according to Supply & Demand Chain Executive, recent 2021 findings showed:
- 41% of firms surveyed reported needing to expedite shipping to keep critical supply lines flowing.
- 36% are losing revenue due to supply shortages.
- 11% experienced brand damage directly resulting from supplier issues.
- Only 26% can predict risks in their supply base.
3. Predictive Insights Help Shippers Find Capacity in Cooling Markets
Predictive analytics grow “smarter” with time. This is due to the ability of aging data to generate more views into historic and real-time trends based on the sum of information. Moreover, the increased use of artificial intelligence (AI) and machine learning throughout the supply chain tech stack helps shippers identify possible options for improvement, such as expanding the carrier network and leveraging digital freight matching tools. Regardless, the ability to understand market trends is also critical to know where to look for available capacity too. After all, some markets may experience cooling trends while others ramp up in conjunction with the release of the latest technology trends and data-driven systems.
4. Applying Shipping Analytics at the Dock
Achieving and maintaining true visibility features continues to add resiliency to the supply chain. Real-time data insights and the ability to apply shipping analytics to account for changing arrivals will naturally lend themselves to improved dock management and reduced stress on any supply chain manager. This full view of data and more accurate ETAs help to reduce delays in unloading or loading, which effectively increases capacity within your network.
Having the most accurate estimate on ETAs can benefit dock management by allowing shippers to pull the data needed to avoid late arrivals and departures if possible. Along with this, dynamic rerouting services can help accommodate schedule changes and avoid missed deliveries and pickups. It all occurs while making the most of each individual leg of transportation.