At a time of growing supply chain complexity and ever-increasing demands for transparency, companies are looking for ways to gain better visibility into the movement of goods, supplier performance, and potential risks. One concept that has gained increasing importance in recent years is the logistics Control Tower. What does this term actually mean, and where does its practical value lie? We discussed this with Svatopluk Cimpa, ECT Manager at Yusen Logistics.
From shipment visibility to active management
The term Control Tower is used quite frequently today. Sometimes it refers to sophisticated management, while at other times it is merely a new name for shipment tracking. What should we understand by it?
At its core, a Control Tower is a central supply chain hub that connects data, technology, processes, and people. Rather than simply tracking shipment locations, it offers end-to-end visibility across the entire logistics flow—flagging disruptions, evaluating their impact, and coordinating real-time solutions.
So, as I understand it, a map showing truck movements or an overview of shipments does not in itself constitute a Control Tower.
Exactly. Data availability alone does not mean that a company has its supply chain under control. The information must be placed in the context of a specific order, production plan, inventory level, or customer commitment. Only then is it possible to determine whether intervention is necessary.
Can you give a simple example?
Consider a manufacturer sourcing daily from hundreds of suppliers across Europe. If a critical component gets delayed, GPS coordinates alone won’t solve the problem. Management needs to know if production will stall, which customer orders are at risk, and whether to reroute, reprioritize, or adjust schedule lines. That shift—from knowing where something is to deciding what to do—is how raw visibility becomes active management.
Who benefits most from such a solution? Is it primarily relevant to global corporations?
The decisive factor is not the size of the company itself, but the complexity of its network. We see the greatest benefit where multiple suppliers, carriers, countries, distribution centres, cross-docking facilities and different transport modes merge. The automotive industry is a classic example but the core principles apply to industrial manufacturing, retail, the high-tech sector, or a mid-sized company with an international supply network.
How can a company’s management recognize that its existing approach to managing component deliveries or inventory is no longer sufficient?
The initial warning sign is often a classic paradox: a company drowns in data yet lacks a clear, real-time operational picture. With information fragmented across internal systems, carrier portals, spreadsheets, and inbox threads, logistics teams waste more time hunting down data than actually managing supply flows.
In other words, the problem may not be a lack of data, but rather its incorrect interpretation?
Yes. Another common red flag is a purely reactive mindset, tackling disruptions only after they strike. The core issue isn’t just that a delay occurred, but how long it took the company to notice. If you only realize a part is missing when the assembly line stops, your most cost-effective options are already gone. A Control Tower buys you critical lead time to act before a delay turns into a crisis.
Data in context
How do you determine which data is truly important?
The value of data lies not in its volume, but in its relevance, quality, and timeliness. Information that a shipment will be delayed by six hours may not in itself indicate a problem. However, if it is linked to production scheduled for the following morning and there is no buffer stock in the warehouse, an ordinary delay becomes a critical event.
The aim is to highlight what is deviating from the plan, what the potential impact may be, and which situation requires a decision. The reliability of the inputs is equally important. If data is missing or contradictory, this must be visible. Otherwise, the result is merely a picture that looks precise but is in fact, incomplete.
From the outside, a Control Tower may appear to be a kind of control centre for resolving day-to-day supply chain problems. Does that reflect reality?
That view is far too limited. Control Towers are playing an increasingly vital role in tactical and strategic planning. Whether deciding where to open distribution hubs, structuring regional flows, or assessing the ripple effects of changing suppliers, plants, or freight modes, companies need reliable data, scenario modelling, and network design to guide those choices.
How, then, are the individual planning levels interconnected?
At the strategic level, decisions are made about the long-term design of the network. At the tactical level, specific flows, frequencies, consolidation points, and capacities are defined. The dynamic level responds to current demand and the actual availability of capacity. If these layers are separated, the long-term network design may be theoretically sound, but day-to-day operations will not be able to make effective use of it. Connecting them makes it possible to manage the supply chain as a single whole.
The real cost of logistics
When it comes to costs, companies often focus mainly on transport prices. Is that not ultimately the simplest and most measurable route to savings?
It is the most visible but not always the most significant. The transport rate is only one part of the total cost. Inventory, warehousing, volume of handling operations, expedited shipments, supply disruption risks and the capital tied up in materials in transit must also be considered. Cheaper transport does not necessarily mean a lower-cost supply chain if it also extends response times or requires higher safety stocks.
Where, then, is the greatest practical scope for change and cost savings?
Often, it lies not in further negotiations over the price per kilometre or transported unit, but in changing the overall logistics architecture. One example is importing components from Asia for several European plants. Instead of maintaining high inventory levels at each plant, part of the stock can be positioned at a central European location and released according to actual consumption. If the model is properly aligned with delivery terms and the management of logistics partners, it can improve cost transparency, shorten response times, and reduce capital tied up in inventory. A suitably designed model can preserve the benefits of minimizing risk and cash-flow requirements for the customer, while simultaneously providing greater control over the logistics solution, standards, and applied rates.
How would you describe a healthy supply chain? Is it one in which as few problems as possible arise?
Not necessarily. In today’s volatile landscape, disruptions – from capacity shifts and demand surges to unexpected climate or geopolitical events, are inevitable. What truly defines a healthy supply chain isn’t perfection, but speed of detection, assessment, and response. Ultimately, health comes down to transparency, resilience and adaptability.
AI supports decisions. People remain responsible.
Today, almost every discussion about logistics sooner or later turns to AI. Some claim that most operational decisions will soon be automated. Do you agree?
Artificial intelligence can process large volumes of data quickly, identify recurring patterns, and flag deviations that a human might easily overlook. It can support ETA prediction, problem categorization, root-cause analysis, and prioritization. However, it does not itself bear responsibility for operational decisions.
Why not? If the system has enough data, should it not be able to select the best option?
It can prepare and compare options very effectively. However logistics situations often involve circumstances that are not fully captured in the data, such as the critical importance of a specific material, the delicate balance between cost and the risk of a production stoppage, the availability of alternatives, or specific customer priorities. The ideal approach is therefore a combination: technology identifies the risk and proposes scenarios, while a human decision-maker assesses the broader context and takes responsibility for the decision and its execution.
Beyond reporting dashboards
Finally, what is the most common myth you hear about Control Towers?
The biggest myth is that Control Towers are just overpriced reporting dashboards. If a tool only presents static data, that critique is entirely fair. But a real Control Tower goes beyond reporting. It actively flags anomalies, evaluates business impact, and orchestrates corrective action. Another misconception is that an ERP or TMS can do the job alone. While those platforms manage specific execution processes, a Control Tower bridges disconnected systems and partners to turn fragmented data into unified, coordinated decisions
Thank you for the interview.
