Data has long been seen as the solution to many of the supply chain’s biggest challenges – and for good reason. When harnessed effectively, it can reveal inefficiencies, uncover risks, and drive faster, smarter decisions. But despite its potential, most supply chain teams still rely heavily on spreadsheets and operate within fragmented systems spread across partners, geographies and platforms.
Although commonplace, disconnection is a barrier to progress. As artificial intelligence becomes essential to competitiveness, companies that are unable to bring their data together will fall behind. Ultimately, AI can’t operate on siloed, inconsistent information.
When supply chain data is unified, teams can move from reacting to issues to anticipating them. Predictive analytics, anomaly detection, and real-time optimization become possible. And, over time, autonomous agents can begin to manage logistics, relationships and risk. In a nutshell, the supply chain has always been complex as it has huge challenges. But a large amount of them are solvable with clean, unified data. Complexity doesn’t need to result in inefficiency. Those who invest now in consolidating and structuring their data will be the ones who lead the next era of AI-enabled logistics.
Overcoming disconnected data easier said than done
Disruption is an unavoidable reality of supply chains. Port congestion, labor disruption and tech risks like cyberattacks can all cause delays on any given day. Naturally, attempting to coordinate plans across a global network of carriers, suppliers, warehouses and customers can be complex. To compound matters, supply chains often involve multiple fragmented systems too, with different partners using different tools both internally and collaboratively.
The result is that data is often duplicated, inconsistent, or out of date. As such, teams spend valuable time reconciling numbers instead of focusing on decisions. This creates a lag between what’s happening in the supply chain and what managers can see, meaning that when disruption hits, delays, costs and stockouts can mount up quickly.
Accurate, unified logistics data is the foundation for solving many of the supply chain’s biggest pain points. Rather than just providing visibility, modern platforms enable automated workflows that streamline operations across partners and regions. While many systems still struggle to communicate, and budget or implementation challenges remain, connecting and standardizing data allows companies to reduce manual effort, improve decision-making, and respond to issues faster and more reliably.
Even with a strong data foundation, moving away from spreadsheets and email isn’t straightforward. Many digital solutions over-promise and under-deliver. At the same time, AI tools are raising expectations, offering valuable insights with minimal input. Implementing new platforms requires a careful balance: enhancing efficiency and enabling automation while keeping day-to-day operations running smoothly.
Steps to build connected, reliable data
The first step in connecting data is understanding where it is. Supply chain managers should start by mapping out where shipping and logistics data lives today, whether that’s in ERP systems, spreadsheets, email inboxes, or across various partner platforms. Data sets can then be standardized so they can be shared across teams and tools. While this self-assessment is key, manual processes like data entry and sharing lack the speed, efficiency and accuracy that modern supply chains need.
What’s needed are cost-effective platforms that can easily integrate with a range of business-critical systems and join up partners and stakeholders. But from inventory management to logistics planning platforms, there are a variety of options on the market. So, finding the right solution depends on assessing several factors.
Considerations should include:
- Can it integrate with the core data platforms you identified?
- Can you access all relevant logistics data and shipping documents on a live tracking dashboard in one location?
- Can you easily share these dashboards with various partners and stakeholders?
- Does it automate data entry processes?
- How quickly can the platform be up and running, and how soon will it deliver measurable value?
- Can it answer complex operational questions, such as which shipments are at risk of detention or demurrage fees in the next seven days?
- Is there a reasonable implementation timeframe that minimizes impact to operations?
- Are there any hidden platform fees?
When you find a platform that is suited to your needs and unifies your data, you can then innovate with AI.
Laying the foundations for AI
AI is only as good as the data it has – fragmented inputs lead to weak outputs. With supply chain data consolidated, however, teams can transform their operations using the technology. By accessing data from one location, AI can build far more efficient and proactive strategies, helping to support tasks like next best actions, automated notifications, smart routing, supplier management, forwarder performance reviews and risk monitoring.
For example, if supply chain managers have a centralized data set that has all of the ETAs and ATAs of every carrier they use, they can use AI to analyze this data and accurately assess carrier performance with ETA accuracy reports. This allows them to benchmark transit times and build objective performance insights that guide decisions around what suppliers, routes and ports to use.
This foundation then paves the way for more advanced AI models like agentic AI. AI agents are able to act autonomously and take actions on behalf of a supply chain manager. So, instead of AI suggesting the best carrier and route to use, for instance, the AI agent automatically confirms these options and arranges them for the company. Clearly, this capability holds vast potential to mitigate disruption in supply chains in a highly efficient way. But again, agentic AI’s success rests on the interoperability of systems and being able to access unified data.
Connected data is everything
There are many issues beyond the control of supply chain managers. It’s a tough, unpredictable world to navigate. But while disruption can be unavoidable, disconnected data isn’t. With manual processes and fragmented systems woven into supply chain operations, companies need cost-effective digital solutions that can consolidate their data into one platform.
By finding the right platform, supply chain managers can connect their data, build real-time logistics visibility, and establish the foundations needed to harness AI. And not only can they use AI to guide decision-making, but the arrival of AI agents presents new opportunities to manage certain tasks with minimal human input.
Ultimately, connected data gives companies the ability to proactively mitigate disruption and the foundation to compete.
