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The complete guide to freight data analytics

As a shipping company, you operate on multiple levels and base important decisions on purchase orders, shipment costs, bills of lading, invoices etc. But pulling all this information together could be a hassle. 

With freight data analytics, you can bring all of your data in one place, enabling you to identify patterns, implement strategies, and make informed decisions more easily. 

What is freight analytics?

Freight analytics is collecting, analysing, and interpreting data related to your freight operations. This data encompasses various aspects of your supply chain, providing insights to help you optimise costs, improve efficiency, and gain a competitive edge. 

Examples of freight data include:

  • Shipment details: Origin, destination, weight, dimensions, mode of transport (e.g., truck, ship, air)
  • Cost data: Transportation costs, fuel surcharges, terminal fees, insurance costs
  • Performance data: On-time delivery rates, dwell times at ports, route optimisation metrics
  • Inventory data: Inventory levels at warehouses, stock movement patterns, lead times
  • Customer data: Customer purchase orders, delivery preferences, feedback

How does freight data management work?

Think of your freight forwarding operations as a complex system, constantly generating shipment, cost, and logistics data. Freight data management organises all this information. Steps include:

  • Data collection: Streamlining the process of gathering data from various sources — such as transportation management systems (TMS), electronic data interchange (EDI), and telematics devices — ensures a comprehensive data capture.
  • Data integration: By integrating data seamlessly from disparate systems into a central repository, you foster consistency and eliminate data silos that can hinder analysis.
  • Data cleansing: By identifying and rectifying errors, inconsistencies, and missing data points, you contribute to the accuracy and integrity of your data.
  • Data governance: Establishing clear policies and procedures for data access, security, and maintenance safeguards the integrity of your data and mitigates potential risks.

Discover how technology is changing freight forwarding.

Benefits of freight forwarding analytics

By analysing vast datasets containing shipment details, logistics metrics, and market trends, freight forwarding companies unlock powerful insights leading to:

1. Cost optimisation

Analysing historical data — inefficiencies in routing, selection of carriers, or fuel consumption — allows you to identify the true drivers of their freight costs. Armed with this knowledge, you can take targeted actions to reduce these costs. For example, optimising routes minimises mileage and fuel usage, while negotiating with carriers based on data-driven insights can lead to more favourable shipment pricing. 

Proactive freight data analysis also helps identify and avoid unnecessary surcharges, such as fuel adjustments or detention fees. These seemingly small savings can accumulate cost reductions over time.

2. Enhanced efficiency

Real-time tracking provides immediate visibility into shipments, enabling proactive solutions for delays. Imagine a scenario where there is a potential delay during transit. Integrating freight data and analytics provides improved communication and collaboration within the company. McKinsey estimates that inefficient interactions within freight operations can contribute up to 19% of total logistics costs, translating to annual losses of up to $95 billion in the United States alone. 

Teams need to be able to share insights, make informed decisions together, and respond to changes. However, critical shipment updates sometimes get lost amidst a constant stream of generic messages, hindering timely decision-making and impacting overall maritime efficiency

By integrating freight data analytics, you streamline shipping communication. For example, through intelligent filtering and content prioritisation within emails, freight forwarders instantly notify team members of potential delays, route changes, or other crucial updates, eliminating the risk of information overload. 

3. Better risk management

Data empowers freight forwarders to navigate the inherent risks associated with global logistics. 

Here's how:

  • Proactive disruption management: Analysing real-time and historical data on weather patterns, traffic congestion, and geopolitical events allows for proactively identifying and mitigating disruptions and taking necessary precautions.
  • Enhanced compliance: Freight forwarding analytics are a powerful tool for ensuring adherence to customs regulations and other legal requirements. By leveraging this data, freight forwarders can minimise the risk of delays, penalties, and reputational damage associated with non-compliance.
  • Improved safety: Analysing data on accidents and near misses empowers freight forwarders to identify safety risks. By implementing preventive measures based on these insights, they can ensure the safety of their drivers, cargo, and the public.

4. Improved customer satisfaction

A KPMG survey shows that 67% of supply chain professionals believe meeting customer expectations is a growing challenge. Analysing customer feedback and shipment data allows companies to pinpoint and address pain points. For instance, identifying recurring delays on a specific route can lead to targeted improvements, directly enhancing the customer experience. Using predictive analytics and by analysing trends and buying patterns, it's possible to adjust inventory in anticipation of demand surges, ensuring customers are never left wanting.

Imagine a scenario where a customer inquires about the status of their shipment via email. An intelligent email management system can automatically identify the relevant shipment details and provide an immediate update based on real-time tracking data. This eliminates the need for the customer to wait for a manual response, fostering a sense of efficiency and attentiveness.

5. Increased sustainability

UNCTAD reports that, while 99% of the world's shipping fleet uses traditional fuels, 21% of new orders are for ships that use alternative fuels, pointing towards a shift to more eco-friendly maritime transport. 

Freight analytics empowers shipping businesses to embrace sustainable practices. By analysing data on fuel consumption, route efficiency, and mode of transport, you can identify areas for reducing the carbon footprint — for example:

  • Implementing fuel-efficient vehicles
  • Optimising routes to minimise mileage
  • Exploring alternative transportation options like rail 

Optimizing packaging presents another opportunity for data-driven sustainability improvements. After analyzing freight data on product size, weight, and damage rates, you might decide to use less packaging — benefiting the environment and lowering costs. Smaller, right-sized packages take up less space, potentially reducing shipping fees, fuel use, and storage needs, too.

Learn how to advance your digital transformation with maritime analytics.

Make the most out of your freight forwarding data with Sedna

Sedna delivers an AI-driven email management system that is purpose-built for the freight forwarding and logistics sector. Our platform Stream goes beyond basic automation – it acts as your intelligent assistant, freeing your team from:

  • Manual data entry: Stream automates data extraction from emails, eliminating errors and saving valuable time.
  • Sifting through endless emails: Stream's intelligent filtering and prioritization ensure your team receives only the most relevant information about shipments, minimizing information overload.
  • Reacting to delays: Stream proactively identifies potential delays based on real-time data, allowing your team to take swift action and keep customers informed.

Unlock the full potential of your freight data analytics. Book a Sedna demo.

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