The Role of Data Analytics in Freight and Logistics

No matter what part in which you operate, if you operate within a supply chain, it’s likely that you’re struggling with the same issue as most other organizations: visibility. Or rather a lack thereof. Whether you’re a carrier, 3PL, freight forwarder, freight broker, or NVOCC, chances are you’re struggling to obtain full visibility over all of your shipment operations.?

As it’s so interconnected, a single setback in the supply chain can create a ripple effect all along it, resulting in frustrated organizations unable to pinpoint where their shipment is and why it’s delayed or impacted. It all comes back to centralized visibility. A lack of data centrality and visibility means you’re left not only with knowledge gaps but with process gaps too.?

Being unable to identify where your operations are delayed or compromised and why leaves you disempowered and unable to take appropriate responsive or preemptive action to solve problems, mitigate risks, manage issues in time, and predict and prepare for an influx of shipping demand.?

Trying to manually sift through the thousands of datasets you’re receiving daily from both suppliers and shipment partners is an impossible task, not to mention the best use of your team’s time. The solution lies in automation, but not just any automation solution - you need data analytics on your side.?

The power of data analytics

What is data analytics? Simply put, it’s the automated process of collecting, processing, structuring and analyzing big datasets by a machine. It can produce quick insights, identify trends, discover useful information, and support decision-making within organizations.?

AI-powered analytics takes it a step further. Instead of a machine simply processing data and producing outputs, advanced analytics provide suggestions, recommendations for best practices and flag potential risks as well as position ideal opportunities. Generative AI, in particular, can use data to create entirely theoretical supply chain issues and potential problems and use them for risk modeling of existing supply chain operations, as well as provide best practices for mitigating them.?

Data analytics within the freight and logistics industry

Within supply chain operations and management, data analytics can become one of your most powerful business assets. The use cases are virtually boundless, meaning data analytics can improve operational efficiency at every point of the supply chain.?

Within planning, supply chain organizations can leverage advanced analytics to identify optimal routes, predict potential route disruptions, and use demand forecasting to plan for surges in demand accordingly.?

For supply chain management, analytics can help organizations track their shipments across the supply chain in real-time, enabling them to know their shipment location at all times. This means that if any disruptions occur, they can respond quickly. They can also communicate more easily with supplier partners without a lack of visibility into where issues are arising.?

Data analytics can also help with supply chain optimization, giving organizations the insight they need that helps them reduce unnecessary costs, enhance their processes, and provide a more personalized customer experience to shippers via real-time data updates on shipment tracking.?

In short, data analytics has the power to enhance your entire supply chain, from beginning to end.?

Implementing data analytics within your business

The key to successful leveraging of data analytics lies in your strategic approach. Trying to implement advanced analytics software is impossible if your data is siloed across separate, disconnected systems that don’t “talk” to each other. Your analytics capabilities may also be compromised if your data is not in a unified, usable structure beforehand.?

To successfully implement data analytics as a business intelligence strategy, you first need a dynamic data management platform or central repository to house your freight and supply chain data. On top of this, you need to ensure that your data repository can “talk” to the analytics software you’re planning to use or already use. If they don’t it could end up becoming a cost sink, and require more upfront investment to build the tech stack necessary to do so.?

A far simpler solution would be to opt for a data management platform that does it all. Stargo is a dynamic all-in-one data management platform that structures, enriches, and centralizes your data.?

Offering advanced analytics as a built-in feature, Stargo provides full visibility and in-depth reporting into your supply chain operations. This allows you to identify gaps, risks, and opportunities within your supply chains, as well as develop preemptive strategies for solving them. Stargo gives you full visibility into every part of your supply chain using aggregated, real-time data for swift decision-making.?

Book a demo and learn how Stargo’s AI-powered analytics and other key features can help you optimize your supply chain management.?