Improving Performance with Supply Chain Predictive Analytics

Supply chain predictive analytics are like a crystal ball for your transportation cost control efforts.

Supply chain predictive 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). It helps you keep your team informed and responsive. Companies that can provide reliable tracking services, accurate ETAs, real-time shipment status and location become go-to brands.

The last thing customers want is a notification that a package will arrive late or, even worse, was delivered to the wrong location. This is especially true in the case of B2B transactions where errors lead to lost customers. 

However, one scenario is worse: customers do not receive any updates. 

That’s why predictive shipping analytics are critical for preventing miscommunications and keeping everyone informed. They can help avoid stockouts and added delays, too.

With peak season approaching and the proliferation of e-commerce driving increased demand for delivery services, reliable and accurate ETA data becomes a top priority. 

Let’s take a closer look at why, and how shipping analytics can enhance capacity planning. We will also examine the value of shipping analytics in tracking shipment ETA.

1. Use Shipping Analytics for Continuous Improvement

Supply chain predictive analytics provide a view of what will happen that day based on current conditions. 

Having this information offers the possibility of correcting mistakes before they happen. Supply chain predictive analytics can be combined with descriptive and diagnostic insights to forecast and identify improvements needed. Next steps to achieve a positive outcome become apparent as well. 

Of course, part of this depends on having the ability to secure capacity when necessary. Peak season brings more capacity stress than other times during the year. As a result, it’s imperative for shippers to access large swaths of analytics that can help identify weaknesses and strengths.

2. Increased Visibility Reduces ETA Confusion

Visibility remains a priority for supply chain managers. During the peak seasons of shipping, visibility is vital to increasing 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 survey findings:

  • 41% of firms 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

Accurate supply chain predictive analytics based on real-time supply chain data can predict more precise lead time and develop solutions to lead time variations. Additionally, having accurate ETAs and shipping analytics will help to continuously strengthen throughput and avoid tarnished customer experiences.

Predictive analytics grow “smarter” with time. This is because aging data can 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. Examples include expanding the carrier network and leveraging digital freight matching tools.

Regardless, market trends awareness is critical finding available capacity too. After all, some markets may experience cooling trends. Others ramp up in conjunction with the release of the latest technology 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. It allows shippers to pull the data needed to avoid late arrivals and departures if possible. Along with this, dynamic routing services help accommodate schedule changes and avoid missed deliveries and pickups. It all occurs while making the most of each individual leg of transportation.

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Put Advanced, Supply Chain Predictive Analytics to Work

Technology continues to evolve, and data increasingly becomes more crucial to effective capacity planning and shipment execution. Partnering with a reliable TMS vendor should be a top priority. 

It is time to put the power of supply chain predictive analytics and a reliable, fact-based ETA to work by tapping into the expertise and power of MercuryGate.

Learn more about how predictive capabilities come together in our TMS


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