In an interview with the “LogTech Podcast,” industry expert André Kaeber presents a series of provocative theories that can serve as early warning indicators for systemic problems in any SaaS company. He argues that many companies are trapped in silos, clinging to outdated models, and that the biggest hurdle to real progress is not budget, but their own mindset. This article distills seven of these uncomfortable truths that every executive should know.

1. Thesis: Your growth problem is not a sales problem, but a system error.

When the numbers aren’t right, the sales department is often the first to be blamed. Kaeber exposes this as dangerous short-sightedness. The problem is not weak sales, but a company that operates in silos. Sales, marketing, product, and management work in isolation instead of questioning the entire “target operating model.” Weak sales are rarely the cause, but usually only the symptom. The fatal consequence of this misdiagnosis: measures such as laying off the sales team only treat the symptom, waste valuable resources, and further distance the company from a real solution.

It is almost never just one issue or problem in one department! Often, it is not the “right” skills that are needed. I have frequently seen companies rely on people who have been successful in SaaS before, but who lack the basic tools to be successful. They are highly specialized, but not in the areas that the company currently needs!

For managers, this means that an honest audit does not begin with the sales dashboard, but rather with the organizational chart, existing skills, and lines of communication between departments.

2nd thesis: The great productivity lie – more systems, fewer results.

One of the most critical diagnoses is that productivity in many industries has stagnated or even declined over the past 20 years! And this despite the introduction of countless software solutions such as TMS, WMS, and MES. Kaeber calls this “apparent optimization.” This phenomenon reveals a massive misallocation of capital: enormous sums have been poured into technology that has not achieved any measurable increase in productivity. As an example, he cites a WMS/TMS solution whose implementation costs rose from 650 to 1,500 person-days, just to stay technologically up to date without improving core functionality. It is precisely this capital, which flowed into maintaining the status quo, that is now lacking for the disruptive innovations that threaten these companies today. We are increasingly dealing with a kind of swarm stupidity! Just because my CIO/CDO colleague at Company XYZ does it this way doesn’t mean it’s right!

Companies must therefore ask themselves whether their IT budgets are financing innovation or merely perpetuating the costs of a missed transformation. In the future, the specialist department will need to be involved much earlier on!

3rd thesis: Riding dead horses – The danger of technological ignorance.

Many SaaS companies are clinging to business models that are on the verge of obsolescence due to developments such as AI. They are “riding a dead horse,” according to Kaeber, trying to keep a fundamentally outdated system alive through incremental improvements. The key here is to realize that it’s not about optimizing existing processes, but having the courage to throw them completely overboard. This requires the radical honesty to admit that your own business model has an expiration date.

The strategic question is not how to improve the existing system, but whether we have the courage to shut it down before the market does.

4. Thesis: The biggest hurdle is not money, but mindset.

Contrary to popular belief, it is not a lack of capital that is the biggest obstacle to innovation, but rather a rigid mindset. According to Kaeber, in Germany in particular, a mentality characterized by security and safety prevents bold, forward-looking decisions. There is a lack of “future managers” – people who are not concerned with managing the status quo, but with the challenges of logistics in 2035. The technology for the next leap forward is often available, but the collective mindset prevents its implementation.

Technologically, we are ready for new developments in many areas, but our mindset does not allow it because our systems are characterized by security.

Managers must therefore first question their own risk tolerance and that of their organization before discussing technological roadmaps.

5. Thesis: The ego trap – Why founders are often their own worst enemies.

The maturity of a founder is not demonstrated by being able to do everything, but by recognizing when the company needs a different type of leadership than he himself can provide.

6. Thesis: Speed is the new currency – from months to weeks.

Long implementation times are a clear warning sign in the modern SaaS world. A provider who cannot demonstrate their solution within weeks rather than months is no longer competitive. Kaeber introduces the crucial but often overlooked concept of “redundancies”: How quickly can a customer switch from one service provider to another within the software? Today, this flexibility is more important than an endless list of features. The most important lever for software providers is not the development of the next feature, but the radical reduction of implementation time and the increase of interchangeability within the system.

The crucial question for every SaaS buyer is no longer “What can your software do?” but “How quickly can I achieve added value and, more importantly, how quickly can I switch if I need to?”

7. Thesis: Trust beats metrics – The underestimated power of the community.

In an uncertain and rapidly changing technological landscape, trust is one of the most important currencies. It cannot be generated in the short term through marketing metrics, but must grow organically over time. Building communities and thought leadership is therefore a valuable long-term strategy, but one that is often neglected in the German logtech scene. Genuine community building is based on personal contact and authentic give-and-take – in contrast to pure “popcorn cinema” formats, where consumption is purely passive.

In an era of AI-generated arbitrariness, an authentic community becomes the only competitive advantage that cannot be copied.

The message is clear: real progress does not come from the next software update or a new sales strategy, but requires a fundamental change in thinking, culture, and strategic direction. It’s about asking uncomfortable questions and honestly assessing whether current efforts are merely serving to keep alive a system that has already had its day.

So the crucial question is not whether you will adopt the next technology, but rather: Are you prepared to get off your dead horse before it’s too late?

The post 7 uncomfortable truths for SaaS companies (and why your growth problem isn’t in sales) first appeared on André Kaeber.

My first encounters with a transport management system (TMS) date back more than 20 years, to 2003 to be precise. At that time, I was working as a consultant in the field of SAP Supply Chain Execution, primarily for industrial companies, i.e., shippers. There, I became familiar with all aspects of transport management: from inbound processes, including imports, to outbound scenarios, to complex multi-site networks in which strategic, tactical, and operational transport planning had to be closely interlinked.

My focus on the operational, holistic management of transports was particularly influential. It was not just a matter of planning individual transports or calculating freight costs, but rather of taking an end-to-end view: How do I integrate the warehouse, how do I manage the supply to a plant, how do container cycles work, how do I optimize loading space, how are machines, assemblies, and equipment transported optimally, and how do I keep service levels and costs under control? These questions shaped my everyday work and continue to influence my thinking about TMS to this day.

From today’s perspective, the SAP R/3 functionalities at that time were limited, but they had one decisive advantage: they could be implemented quickly, were highly integrated, were sufficient for many companies, and could also be expanded selectively with a little programming. We were often able to implement functioning solutions within a few weeks, sometimes even days. For many shippers, this was a real competitive advantage because they could bring transparency and standardization to their transports with manageable effort.

The broader context

While I base my experiences on projects with shippers, Graham Parker paints a picture of the global TMS evolution in his article “Why Global Shipping’s Brain Needs a Total Rewrite” (2025). He recalls that TMS emerged in the 1990s as an extension of ERP systems, driven by the explosive growth of global trade. SAP was a pioneer in this field, with Oracle following soon after.

Parker describes the years 2005 to 2015 as a kind of “supercycle” for TMS implementations. Systems were introduced worldwide because global supply chains were becoming increasingly complex, customers were demanding greater transparency and speed, regulatory requirements were increasing, and costs were coming under greater pressure.

While Parker examines this development from a macro perspective, looking at global trade flows, BCO shippers, and international trade lanes, I have witnessed the micro perspective of shippers: the operational reality in industry and trade. This is where companies did not plan their transports theoretically, but had to actually manage them day after day across plants, countries, and modes of transport.

Classic TMS: Useful, but no longer sufficient

From a shipper’s perspective, traditional TMS systems represented a huge step forward at the time. For the first time, it was possible to view and manage transports holistically. However, the limitations soon became apparent:

• Interfaces were cumbersome, real-time information was hardly available.
• Lack of web capabilities and collaboration options (e.g., time slot management or WEB EDI)
• Multi-site planning was only possible with considerable customization.
• Workflows were often too rigid to respond flexibly to changes.
• No strategic components in location planning or freight contracts
• Limitation to transport execution vs. planning (lack of heuristics or optimization solutions)
• Statische Stammdaten (Routen & Entfernungsnetzwerke) anstatt dynamischer Routen etc.

Today, 20 years later, many shippers still use these old systems, often with add-ons! But the world has changed: supply chains are more global, volatile, and complex than ever before. Data-driven decisions and automation are a must, not an option!

Power of transformation

The forces at work today, which I sense in my practice not only among shippers:

1. The natural upgrade cycle

Many TMSs introduced during the supercycle phase are now technologically obsolete. Shippers are faced with a decision: continue working with outdated systems or take the plunge into the new.

2. The SaaS (R)evolution

Cloud-native systems enable genuine collaboration across locations, regions, and partners for the first time. For shippers, this means a consolidated view of inbound, outbound, and import shipments in real time. However, many systems are rather limited from the shipper’s perspective, as they are specialized, for example, only for trucks, hardly ever for rail, and often there is a misunderstanding between shipping and transport management!

3. The API and AI Revolution

API-first approaches and AI agents are radically changing the logic of transport management. Shippers can orchestrate their transports across different plants, carriers, and regions without having to operate a monolithic system. However, companies often still lack the knowledge to develop realistic strategies for the future!

Agentic AI Workflows – the next step

This is precisely where my observations over the past few months come in: for me, agentic AI is the logical next step in development.

• Freight cost verification is handled by AI, which instantly compares invoices, rates, and services.
• Transportation execution is dynamic: agents automatically tender, adjust routes, communicate independently with carriers, and manage exceptions.
• Transportation planning becomes a continuous learning process that adapts to disruptions in real time and optimizes scenarios across multiple locations.
• Communication with logistics partners using dynamic interfaces, LLM that communicate with the driver by voice, and AI-supported mapping and interface monitoring!

This changes the role of the TMS: it is no longer a system that maps workflows, but a platform orchestrated by agents.

My assessment – lessons learned from projects

If there’s one thing I’ve learned from over 20 years of TMS projects with shippers, it’s this: technology alone is not enough.

My answer to the question of whether we still need traditional TMS is as follows:

• Technologically: No! Modular, AI-native services are superior.
• Organizational: Not all companies are ready to hand over operational responsibility to autonomous systems, so the transformation alone will actually take years!

The biggest hurdle lies not in IT, but in organization and culture. Trust in agents, governance, and change management are crucial.

Conclusion: Two perspectives, one goal

My review of the shipper world and Parker’s global analysis lead to the same conclusion: we are at a turning point in transport management.

• Classic TMSs have played their part and have been crucial to the progress made over the last two decades.
• But the future belongs to an orchestrated, modular, and AI-driven world in which agents take over operational control and humans focus on strategy, partnerships, and innovation.

The question is not whether we will take this step. The question is how quickly we are prepared to let go of yesterday’s technology and shape the world of tomorrow.

Sources

• Parker, Graham (2025): Why Global Shipping’s Brain Needs a Total Rewrite, Building the next generation of BCO Shipper Supply Chain Software, 18. August 2025.
• Over 20 years of hands-on experience with SAP Supply Chain Execution at industrial and commercial enterprises (inbound, outbound, import, multi-site, operational control).
• Gartner (2024): Emerging AI Workflows in Enterprise Applications.

The post From SAP R/3 to Agentic AI Workflow – My journey through the evolution of transport management first appeared on André Kaeber.

Digitalization has changed or is currently changing many areas of logistics: from warehousing and transport to real-time tracking of global supply chains. In many areas, we are still in the early stages, not least because of the new and often underestimated possibilities and, above all, outdated patterns and ways of thinking, as well as a lack of willingness to invest. And then there is one place that seems like a relic from the analog past: the yard—the last few meters before the gate, which only seem to interest the gatekeeper!

My thesis: After 15 years in yard management and in-depth market knowledge of both yard and plant logistics: Classic yard management systems (YMS) were created in a world that no longer has anything to do with today’s world. They work as they were designed to. However, they are not only inadequate for today’s world and requirements, but their rigidity and isolation increasingly jeopardize the performance of modern supply chains. The time for radical rethinking is now.

Historically, YMS were often confused with slot management systems (even by the providers themselves) and introduced as simple planning and management tools: booking time slots, recording arrival times, managing parking spaces, assigning gates. However, with increasing complexity, global competitive pressure, a focus on sustainability, and the advent of autonomous technologies, the yard is now a strategic bottleneck—and at the same time an underestimated lever for transformation.

Analysis of the innovation backlog: Old systems facing new problems

Many companies have acquired a YMS in recent years in the hope of gaining control and transparency. However, the reality is often different:

🧱 Rigid processes instead of flexible control
Traditional YMSs are rule-based. They map processes that were once conceived in analog form—only now they have been digitized. But real process intelligence? Not a chance. Genuine learning from bottlenecks? Not a chance! Process variance? Project work!

🕰 Lack of real-time capability
Many systems work with outdated interfaces or require manual updates. The result: congestion at access points, lost time, unused resources. At a time when every package is tracked, the yard often remains a blind spot.

🔌 Isolation instead of integration
YMS are often not integrated into transport, storage, and production systems, or only to an insufficient degree. Information does not flow consistently. What is missing is an end-to-end concept—the yard as a fluid part of the chain.

🎭 Buzzwords instead of substance
“Cloud-based,” “mobile-enabled,” “user experience”—many modern YMSs advertise with terms that are more style than substance. Often, these terms simply refer to the digitization of old processes—but no real transformation. Usability that cries out for help and cannot be operated by new colleagues, let alone automated by agentic AI!

💬 The plant manager of an international chemical company summed it up succinctly:

“Our YMS is like a digital clipboard. Everything that used to be on paper is now just a click away—but it doesn’t think for itself.”

Solution spaces and vision for the future: The yard as a living organism

But there is another way. True innovation arises where technology, new ways of thinking, and collaboration come together. The path to the smart yard begins with a paradigm shift:

🚀 1. Platform thinking instead of isolated solutions

A modern yard is not an island, but a hub in a dynamic network. Instead of individual solutions, platforms are needed that connect transport, warehousing, production, and external partners in real time. APIs instead of Excel. Data streams instead of deadlocks.

🧠 2. AI-supported scheduling and forecasting

Why should a time slot be fixed if we can predict the arrival time? Of course, because the warehouse also uses fixed times for staging and picking. This is an argument in favor of our legacy systems! AI can take over ideal control based on traffic data, production status, warehouse information, and priorities—proactively, adaptively, and with the ability to learn. And this applies both internally to warehousing and production and externally to shipping, sequencing, etc.

🌐 3. Digital twins & real-time transparency

Sensors, gate cameras, GPS, and telemetry now provide a wealth of data. But often, this data goes unused. A modern yard ecosystem uses IoT to respond in real time: from the gate to loading.

🦾 4. Autonomous yard management – from human-machine interaction to autonomy

Autonomous vehicles, automatic parking space allocation, digital accompanying documents—what sounds like the future today is already a reality in pilot projects in many places. The vision: a yard that operates independently, recognizes bottlenecks, plans, and learns.

🤝 5. New ecosystems and collaboration as catalysts

Innovation does not happen in isolation. It requires partnerships between logistics providers, tech startups, industrial companies, and consultants—all on an equal footing. Anyone who wants to rethink the yard today must also redesign the way they work together.

🌍 Open source, co-innovation, logistics communities such as Shift³: they create spaces where new solutions can be tested, scaled, and implemented on a broad scale.

Conclusion and impetus: The yard is ready for a new beginning

The yard has long been the blind spot of digital transformation—but this is precisely where enormous potential lies. Companies that have the courage to radically rethink their yard management not only achieve efficiency gains. They also build a strategic competitive advantage by:

• shorter turnaround times
• transparente Prozesse
• more sustainable transport chains
• höhere Zufriedenheit bei Fahrern, Kunden und Mitarbeitenden

🚨 Now is the time to act. Why?

And because sustainability can’t wait—every unnecessary minute on the yard is a step backward for our emissions.

Because technologies such as AI, IoT, and autonomous systems are developing rapidly.

Because the shortage of skilled workers is forcing us to make processes more intelligent and self-managing.

The post Beyond the Gate – Why traditional yard management systems fail and how true innovation in the yard is created first appeared on André Kaeber.

Efficient logistics depend on control systems that enable seamless planning and perfectly coordinated processes. In yard management in particular, a lot comes together: arrival and departure times, goods in and out, allocating parking spaces for trucks, directing them to the right gates… The number of aspects that need to be managed is vast, which is why the market for digital solutions in this area is booming. It’s a growing concern for more and more companies around the world, so it’s not surprising that more and more startups are focusing on it. They all promise to optimize the factory logistics processes that take place between the warehouse and transportation management, increasing efficiency by double-digit percentages. But few take a holistic, global view, focusing instead on regional, industry-specific, and site-specific differences.

But which of these promises can today’s yard management systems really deliver? Which solutions have the potential to significantly impact the future of logistics?

I currently see five trends in the market, ranging from traditional approaches to highly automated and specialized ones. Here’s my take:

1. Dock Scheduling and Digital Registration

Dock scheduling solutions with web-based gate and time slot management enable better planning of loading and unloading times. This type of time slot management significantly reduces wait times, increases warehouse handling capacity, and simplifies collaboration between carriers and manufacturing or distribution companies. The option of digital registration provides additional relief for smaller sites without a large system in the background. However, these often very simple solutions have two weaknesses: first, they often do not support the processes and workflows on the yard site, as the focus is on gate control, and second, the time slots are purely declarative, as the punctuality of the carriers cannot always be guaranteed due to traffic jams and delays.

2. Cloud-based yard management

There are a number of new vendors offering comprehensive yard management solutions. However, these solutions tend to be highly commoditized and not easily customized. There is often limited support for maneuvering processes, and manufacturing companies in particular may find the functionality somewhat limiting. I see weaknesses with many vendors in terms of complex integration and a lack of end-to-end process expertise. Nevertheless, it’s a step in the right direction, because the cloud offers a quick entry into digitalization without having to build a lot of infrastructure beforehand.

3. Yard automation through technology

Solutions currently range from teleoperation (driverless logistics), AI and OCR-based systems to hardware peripherals that control yard resources through cameras or sensors. It is definitely a future model with huge growth potential due to the high level of connectivity, monitoring and digital intelligence. However, much of this is still at the proof-of-concept stage and is therefore still being researched and tested.

4. Yard management as part of a software suite

Another common model is to integrate yard management into an existing software solution, such as SAP. This offers significant advantages over a standalone deployment, such as centralized data processing, increased connectivity, and automation. However, it often requires licensing and can be cumbersome to implement.

5. Yard management systems for specialized processes

As is often the case, there are industry-specific solutions for yard logistics, including hinterland terminals, rail logistics, finished vehicle logistics, port logistics, and more. These solutions are advantageous for addressing specific challenges unique to each industry, although customizable solutions may require additional initial effort. However, the integration potential varies from system to system.

My conclusion

In 2024, yard management should no longer be viewed in isolation, but rather as an integral part of a holistic supply chain and comprehensive logistics IT strategy. Integration with inventory management, warehouse management, and transportation management is critical. When all these systems are connected, they can be perfectly synchronized, resulting in significant synergies. Technologies such as AI and IoT will transform dock and yard management by automating processes and supporting human workers – who will still be needed in the future. What aspect of yard management are you currently working on? Are you facing challenges and need advice? Feel free to contact me directly; I’m here to help.

The post Yard Management: Driving Future Logistics first appeared on André Kaeber.