Too much choice is a common occurrence in our digital world. For supply chain leaders, choosing between the array of options at their disposal, which are themselves constantly evolving, can be so overwhelming that it almost creates choice paralysis. Consequently, any decision taken often lacks context or analysis around its long-term impact.
Shipping alliances are adjusting to better cover trade routes, share capacity and provide the necessary level of frequency and reliability. Routes themselves are changing in line with a shifting geopolitical context, climate events and consumer trends. Port infrastructure is constantly developing too, with innovations such as smart cranes, AI-berth scheduling and an increasing use of green energy all optimizing operations.
All of these ever-evolving trade options lead to a sea of data and choices that add complexity to supply chain leaders’ decision-making. Knowing what carriers provide the best routes and performance reliability in trade off with other metrics like costs and emissions can be a complex activity to calculate, especially when these data points can fluctuate in real time too.
With trade options constantly shifting, connecting data in one place to form a shared supply chain workspace is fundamental for making informed decisions and achieving optimal business performance.
When there’s too much choice
Consider what happened when the Red Sea disruptions forced rerouting in 2024. Supply chain managers suddenly had to compare Cape of Good Hope routes vs. their existing Suez options but lacked unified data to assess which carriers actually performed better on longer routes, what the real transit time differences were, or how costs would shift. Instead of having objective performance data at their fingertips, many resorted to gut decisions based on incomplete information scattered across carrier portals, forwarder emails, and outdated spreadsheets.
This challenge is compounded by constant shifts in the carrier landscape itself. For example, alliances between shipping lines are continually evolving. These carrier alliances create shared capacity in major global trade lanes but can also add opacity – shippers might not always be aware of which vessel their cargo is truly on, making it difficult to track shipments or assess which partner in the alliance is actually delivering the reliability they're paying for.
And as some partner up, others go independent.
It’s not just about the major players. The continuing surge of ecommerce has driven a demand for smaller, faster routes like cross-border trucking, regional air freight and last-mile distribution partnerships. This is joined by digital on-demand freight marketplaces that allow brands to instantly access dozens of carriers and routes. Supply chain managers can book spot capacity in real time, but fluctuating rates and availability increase uncertainty.
Carriers themselves are also adding premium options – guaranteed space, sustainability offsets, faster clearance – that add further choice to decisions. Then, alternative routes, whether via Suez or Panama, are continuously opening or reemerging as geopolitics, energy costs and climate events shift.
Ultimately, this ongoing evolution and expansion of carrier and route options adds complexity to planning, cost modelling and carrier performance management. It’s a choice overload.
Manual burden and complexity
With so many evolving options, organizations can be hindered in their ability to manage, compare and measure their shipment carriers. The use of different partners can create a system of fragmented systems, with each supplier potentially using different tools both internally and collaboratively, like specific carrier portals or sharing data via spreadsheets. This results in data that’s hard to access, outdated, duplicated or inconsistent.
Emails and spreadsheets are a go-to source for communication and sharing data, but their use obstructs data connectivity. So, rather than using insights to make decisions on what carriers and trade routes to use, teams spend their time reconciling numbers and attempting to manage any disruption reactively. Consequently, the picture of what’s happening in the supply chain and what managers are aware of is delayed and always playing catch up.
Due to these complications, companies can end up simply trusting their freight forwarder, perhaps blindly, and favor sticking to what they know (as it’s hard to change forwarders and have the data to back up that change). But this dependency means that if any disruption takes place, costs, stockouts and delays can all spiral at pace. Therefore, what’s needed is a way to unify supply chain data and accurately measure carrier performance.
The mission to unify trade data
The latest supply chain technology available means teams don’t need to wait to receive data from forwarders or jump between carrier portals. AI supply chain workspaces, for example, can now integrate with ERP systems, carrier APIs, and forwarder data feeds to create a single source of truth for shipment and performance data. By collecting and processing real-time data from various touchpoints in the supply chain in this way, managers can access all relevant logistics data and shipping documents on a live tracking board in one location.
Crucially, this unified data is perfect for using AI. It enables the technology to analyze key carrier and forwarder performance KPIs like on-time delivery rates, transit times and emissions, allowing firms to access detailed and objective performance insights on carriers, routes and ports. They can then use these reports to guide, even spell out, decisions on what trade options to use.
With data connected, for example, teams can even tackle more complex operational tasks like identifying shipments at risk of detention or demurrage fees in the next week. They can subsequently share all information directly with various partners and stakeholders via shareable links and avoid the need for time-consuming emails, manual data entry processes and inconsistent file formats.
Unifying data this way also creates the possibility of integrating new AI advancements like AI agents. As these systems mature, AI capabilities can progress from providing performance insights to suggesting optimal carrier and route selections based on your specific performance data and business rules. Governed and used correctly, their use could be transformative for supply chain operations.
Data consistency in an ever-evolving scene
Trade options are ever evolving, and the best performing carriers and routes will continually shift in line with global trends and demand. So much change and choice adds complexity to supply chain decisions and understanding carrier performance, a task already made difficult by manual processes and fragmented data sources and systems.
Real-time data consistency and connectivity is fundamental to measuring carrier performance and harnessing the power of AI. It allows supply chain leaders to make informed decisions, optimize business performance and mitigate disruption efficiently and proactively. Ultimately, it gives them clarity in a scene full of complexity.
