Freight Analytics: How Leveraging Shipping Data Can Help Retailers Master Their Shipping Process
Introduction and Benefits of Freight Analytics
Freight analytics is data about freight performance, offering insight into your supply chain and leading to more informed decisions for your business.
Freight analytics can be predictive, which makes it easier to forecast potential changes, improve operations, and strengthen your risk management strategy. They can also be descriptive, summarizing important data and generating reports that allow you to identify trends and spot patterns more easily.
You can also use prescriptive freight analytics to develop action plans and weigh the potential pros and cons of each strategy before deployment.
In this blog, we will explore freight analytics and how they can help you improve order times, reduce operating costs, and even lower your risks when shipping orders to customers.
Better Decision Making
Freight analytics offer extensive data about your shipments, and they make it easier for you to make data-driven decisions. Information such as shipment deliveries, delays, payment processing, and consumer feedback all play a role in shaping the choices you make as a leader.
With the right freight analytics, you can pinpoint vital details about your operations that help you make streamlined improvements and impactful decisions.
As a retailer, you may find that you get a deeper understanding of your shipping process. How many packages are being shipped on time? How many are arriving late? What number of customers report damages, and did these occur in transit or during manufacturing?
These are just a few questions that freight analytics can answer.
Risk Reduction
A greater understanding of your freight data also allows you to identify potential risks and highlight current challenges in greater detail. This, in turn, allows you to take a more proactive approach to risk management that can save you costs and prevent future disruptions.
For example, predictive freight analytics can help you foresee potential shipping delays, inventory shortages, and disruptions. Rather than solely react to these issues as they arise, you can proactively develop a strategy to avoid damages and losses.
Cost Optimization
Using freight analytics, particularly predictive models powered by AI, can help your business optimize its costs and maximize profitability in several ways. Potential applications in this area include:
Route optimization that improves delivery times and reduces fuel expenses.
Forecasting demands for particular products and adjusting inventory levels accordingly.
Improve carrier billing practices.
Enhanced Customer Service
You may think that freight analytics applications are reserved solely for the logistical side of your operation, but they can also play a fundamental role in improving customer satisfaction.
The deeper understanding analytics provide your organization ultimately allows you to deliver better service to all of your customers. You can have precise information about their order statuses, offer updates via email and SMS, and even use analytics to deliver real-time tracking of their shipment.
How to Use Freight Analytics KPIs to Improve Shipping Progress
The following key performance indicators (KPIs) can be used to help your organization improve its shipping process and boost customer satisfaction in the process. Additionally, optimizing operations around these KPIs can also help improve relationships with carriers and lower your overhead costs.
On-time delivery: Find out what percentage of shipments arrive at their destination on time, and identify common patterns and themes that influence delays.
Transit time: Identify how long shipments are in transit, causes of disruptions, and implement solutions that reduce time spent in transit.
Freight spend: This KPI tells you how much your business is spending to maintain its freight, and it highlights areas that you may address to save money.
Carrier performance: Review carrier performance in terms of pick-up, delivery, and delays to determine which carriers are the most reliable and economical for your organization.
Inventory levels: This KPI helps you stay on top of your inventory at all times, predict surges, respond to increased demand, and avoid paying more for emergency orders or refunding orders for out-of-stock products.
Freight damage and loss: While some damages may be inevitable, you can get a better look at where your most costly freight damages emerge and take proactive steps to avoid them in the future using this metric.
Conclusion
By implementing freight analytics into your business’s management, you can improve every facet of your supply chain. From the moment someone places an order to the precise time it reaches their destination; analytics are powerful data tools that allow you to improve customers’ experiences while supporting your business’s greatest outcomes.
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