Sky-Walker: How the Right Data Drives Confident Decisions in Logistic

When the Right Data Drives the Right Decisions in Logistics

DHL introduced the New Forwarding Environment (NFE), a centralized IT system designed to modernize and standardize logistics processes across its global freight forwarding operations. The ambition was clear: to improve shipment visibility, enable standardized processes, support better operational decision-making, and reduce complexity across regions. On paper, it aligned perfectly with the broader industry trend of leveraging data to drive logistics efficiency.

However, the rollout quickly revealed major challenges. While technically sound, the system failed to fully account for the operational diversity of DHL’s global network. Regional workflows, routing practices, warehouse processes, and customer delivery requirements were not fully reflected in the standardized data model. As a result, operational efficiency did not improve as expected, and in some regions, processes became more difficult to manage. Complexity increased, and the anticipated performance gains failed to materialize. Ultimately, DHL discontinued parts of the rollout and recorded a financial write-off of approximately €345 million.



The failure was not a problem with technology itself. It was a failure to translate data into actionable operational insight.

The NFE system relied on a centralized logic that assumed global consistency across operations. Logistics, however, is inherently variable. It is influenced by regional infrastructure, local regulations, customer requirements, warehouse capacities, and transport network nuances. When systems rely on generalized or incomplete operational data, they risk optimizing for theoretical efficiency rather than real-world execution.



In DHL’s case, the data model supported standardization, but it did not support real-time decision-making across a complex, distributed network. The lesson is clear: having data is not the same as having the right data, and visibility is not the same as actionable insight. Without accurate, contextualized data, even the most advanced systems can produce decisions that look correct on a dashboard but fail in practice.

The challenge for logistics professionals today is not simply access to data. Most companies already collect enormous volumes of information from transport systems, warehouse management tools, and reporting platforms. The challenge is making that data usable. Fragmented or inconsistent data creates delays, misaligned planning, and missed opportunities for optimization.



The real value lies in transforming raw information into insights that can guide decision-making. This requires consolidating data from multiple sources, ensuring accuracy and consistency, and providing visibility into the operational realities of the business. Only then can organizations make decisions that are informed, timely, and aligned with the realities of the supply chain.

This is where platforms like Sky-Walker become crucial. Sky-Walker consolidates operational data into a single, accessible dashboard, giving logistics professionals a unified view of their entire network. Centralizing information, it allows teams to track key performance indicators, monitor execution, and quickly identify inefficiencies or deviations from plan.

Sky-Walker itself does not include AI, but its structured and accessible data environment creates the foundation necessary for advanced analytics or AI-driven tools to function effectively. AI can enhance decision-making, but only when it is fed consistent and reliable data. Sky-Walker ensures that the right data is visible, organized, and usable, enabling professionals to make smarter, evidence-based decisions.

With access to complete and contextualized operational data, logistics teams can respond proactively to challenges, align planning with execution, and maintain service reliability even in complex and variable environments. Decisions become more than reactive responses; they become informed, strategic actions

When data accurately reflects operational conditions, it transforms decision-making. Logistics professionals can anticipate bottlenecks, optimize routes, allocate resources effectively, and maintain service levels. In contrast, relying on incomplete or abstracted data, as in the DHL case, can lead to inefficiencies, operational disruption, and significant financial impact.

The lesson for the logistics sector is clear: decisions must be grounded in reality, not assumptions. A platform like Sky-Walker provides the operational visibility necessary to bridge this gap, ensuring that strategy and execution are aligned.

The DHL case underscores the consequences of data that fails to support operational decision-making. Yet the solution is not to avoid digital transformation or data-driven logistics; it is to implement it correctly.



Sky-Walker addresses this challenge by centralizing operational data, providing clear insights into performance, and enabling logistics teams to make confident, evidence-based decisions. By transforming fragmented data into actionable visibility, Sky-Walker ensures that logistics decisions are informed, timely, and operationally grounded.

In logistics, complexity cannot be eliminated, but it can be understood. The difference between costly mistakes and efficient operations often comes down to the quality and usability of data. Decisions based on the right information can drive efficiency, reduce risk, and improve service reliability, while decisions based on incomplete or misinterpreted data can have significant financial consequences.

Platforms like Sky-Walker provide the foundation for informed decision-making, transforming data from a passive resource into a strategic advantage. By ensuring that visibility reflects operational reality, logistics professionals can confidently navigate complexity and make decisions that truly drive performance.

In logistics, the right data doesn’t just inform decisions it shapes the success of the entire supply chain.