Turning Complexity into Clear Decisions - for Maximum Productivity

How can manufacturers turn growing supply chain complexity into clear, confident decisions? In this behind-the-scenes episode of Supply Chain & Friends, we take you inside the development of STREMLER Realtime Technologies (RTT) and explore how real-time planning, simulation and AI-powered decision support help manufacturers maximize productivity while reducing inventory and improving delivery performance.

Stephanie: Welcome to our Supply Chain & Friends podcast. Today we're talking about Turning Complexity into Clear Decisions for Maximum Productivity. Joining me today are Hans Huber, CEO of STREMLER AG, and our RTT development team: Yasin Baytürk and Selçuk Cabuk. Before we talk about technology, I'd like to start with a personal question.

What fascinates you most about supply chain planning?

Selçuk: What fascinates me most is that supply chain software connects the digital world with the real world. As software developers, we usually write code that stays on a screen. In production planning it's completely different. Every algorithm we develop, every improvement we make to RTT, eventually affects a real factory. It changes production lines, material flows, delivery performance or inventory levels. Knowing that our software has a direct impact on how companies operate is extremely motivating.

Yasin: I completely agree. Most software products remain digital. Supply chain software doesn't. You change one planning rule, improve one algorithm, and shortly afterwards you can see the results in production. Better planning leads to better decisions, and better decisions become visible in warehouses, on production lines and ultimately at the customer. Being able to measure that impact is what makes this work so rewarding.

Hans: For me, the biggest motivation is helping manufacturing companies become more competitive. When we improve planning, we help companies increase productivity, improve delivery performance and use resources more efficiently. That creates real business value and contributes to keeping industrial manufacturing competitive.

If you had only two minutes to explain STREMLER Realtime Technologies (RTT) to a customer, how would you describe it?

Selçuk: RTT is a real-time planning platform that connects all relevant planning information across the supply chain. It integrates ERP systems, forecasts, customer orders, inventory levels, capacities, packaging materials and many other data sources. Based on this information, RTT continuously creates optimized production and supply chain plans. One major difference compared to traditional planning systems is flexibility. Most planning systems force companies into fixed planning intervals such as weekly or monthly planning cycles. RTT adapts to the customer's business. Planning can happen daily, weekly or within any planning horizon that makes sense for the specific production environment. Another important aspect is connectivity. RTT exchanges information seamlessly with ERP systems and other applications, ensuring that planning is always based on the latest available information.

Yasin: I usually describe RTT as an intelligent planning layer on top of the ERP system. It doesn't replace ERP. ERP continues to manage transactions and operational processes. RTT adds intelligence. Whenever something changes—a forecast, inventory level, production capacity or customer demand—RTT immediately recalculates the consequences. Instead of waiting for the next nightly planning run, planners receive updated recommendations within seconds. Traditional MRP systems mainly react to the current situation. RTT continuously looks ahead, identifies future capacity shortages or supply risks weeks in advance and proposes actions before problems actually occur.

Hans: Ultimately, RTT helps companies balance three critical objectives:

• maintaining high delivery performance

• minimizing inventory

• and utilizing production resources efficiently

Finding the right balance between these objectives is one of the biggest challenges in manufacturing—and exactly where RTT creates value.

When do you realize that RTT has really made a difference for a customer?

Selçuk: The most obvious indicator is trust. At the beginning of a project, planners usually double-check every recommendation generated by RTT. They compare the results with Excel spreadsheets and validate every planning proposal manually. Over time something interesting happens. The spreadsheets disappear. Planners begin to trust the system because they consistently see that the recommendations are reliable. RTT becomes part of their daily work rather than another tool they have to verify. That is the moment when software becomes a real decision-support system.

And what impact does that have on the planners themselves?

Selçuk: Many planners spend a large part of their day collecting data, transferring information between spreadsheets and checking calculations manually. RTT automates these repetitive activities. Instead of acting as data administrators, planners can concentrate on evaluating recommendations, making decisions and managing exceptions. Their role shifts from manually creating plans to actively steering the production process.

Hans: Exactly. The real benefit is not only faster planning. It is that planners can focus on the decisions that actually create value for the business instead of spending their time on repetitive administrative work.

We often talk about real-time planning. What does "real-time" actually mean in day-to-day production planning?

Selçuk: In a traditional planning system, changes are typically processed overnight. If a planner changes a production quantity today, the consequences usually only become visible after the next planning run. That means decisions are often based on outdated information. RTT works differently. Whenever a planner changes a production quantity, adjusts capacity or receives new information from the ERP system, RTT recalculates the complete planning situation within seconds. The planner immediately sees the ripple effects—not only for today, but across the coming weeks. If a production line stops, capacity changes or customer demand increases, the consequences become visible instantly. Instead of waiting until tomorrow, planners receive immediate feedback and can react while there is still time to make better decisions.

Yasin: Supply chains are constantly changing. Forecasts are updated. Inventory levels change. Production orders are completed. New customer orders arrive throughout the day. With traditional planning, planners often work with a snapshot that becomes outdated almost immediately. RTT continuously recognizes these events and automatically updates the planning situation. That is what real-time planning really means: decisions are always based on the latest available information.

What makes RTT technologically different from classical planning systems?

Selçuk: Traditional planning systems are usually built around fixed batch processing. Planning happens at predefined intervals—perhaps once per day or once per week. The software assumes that the business follows those fixed planning cycles. But reality doesn't. Different companies require different planning horizons. Some need daily planning, others weekly or even more flexible planning intervals. RTT adapts to the business instead of forcing the business to adapt to the software. Another important difference is its event-driven architecture. Whenever information changes—for example inventory levels, packaging material availability or production capacities—RTT immediately recognizes the event and recalculates the planning situation. Planning therefore becomes continuous instead of periodic.

Yasin: RTT also looks ahead. Instead of reacting only to today's situation, the system continuously evaluates future demand, capacity constraints and safety stock requirements. Potential shortages become visible weeks before they actually occur. Rather than reacting to problems, planners can prevent them. That shift—from reactive to proactive planning—is one of the biggest technological differences.

Which decisions does RTT actually support during a planner's daily work?

Selçuk: Every production decision depends on many interconnected factors.

• Is enough raw material available?

• Are packaging materials available?

• Is sufficient production capacity available?

• Can customer demand still be fulfilled later if production is postponed?

RTT evaluates all of these questions simultaneously. Instead of checking each condition manually, planners receive a clear recommendation: go or no-go. The system only recommends production when all relevant constraints have been evaluated. That creates confidence and significantly reduces planning effort.

Yasin: RTT also answers questions that planners previously had to estimate. For example:

• How much inventory should be built before a planned maintenance shutdown?

• Which products should be produced earlier?

• Which materials are overstocked?

• Where will future shortages occur?

• Should safety stock remain fixed or adapt to demand?

These decisions are transformed from assumptions into measurable, data-based recommendations.

Hans: Production planning is always about balancing competing objectives. Companies want to maximize delivery performance while minimizing inventory and making the best possible use of production capacity. Those objectives naturally conflict with one another. RTT helps planners evaluate these trade-offs and identify the most balanced solution instead of optimizing only one parameter.

One of RTT's most powerful capabilities is simulation. How do what-if scenarios improve decision-making?

Selçuk: Simulation allows planners to test decisions before implementing them. Imagine that a production line must be shut down for scheduled maintenance. Instead of estimating how much inventory should be produced beforehand, planners simply reduce the machine capacity within the simulation. RTT immediately calculates the impact across all affected weeks. The planner can evaluate different alternatives, compare scenarios and determine exactly how much inventory should be built before the shutdown. The same applies to seasonal demand peaks. Before Christmas or other high-demand periods, companies can simulate future demand and determine the required production levels long before the actual demand occurs.

Yasin: That is the real strength of simulation. Companies no longer have to guess. They can evaluate different scenarios before making costly decisions. Whether maintenance is delayed, capacity changes or demand increases, RTT calculates the consequences before the decision is implemented. That makes planning significantly more reliable and reduces operational risk.

Have there been situations where customers were genuinely surprised by what RTT revealed?

Selçuk: Absolutely. Quite often companies focus on what they believe is their biggest bottleneck. RTT sometimes reveals that the real bottleneck is somewhere completely different. For example, planners may assume they need to order more packaging material for one product, while the actual limitation is a raw material shortage for another product several weeks later. Without simulation, those hidden dependencies are almost impossible to detect.

Hans: Another common surprise concerns inventory. Many planners instinctively believe that producing as early as possible is always the safest option. RTT often recommends the opposite. If production can be postponed without affecting delivery performance, the system deliberately schedules it later to reduce inventory and tied-up capital. That initially challenges established planning habits—but once customers understand the reasoning, they quickly recognize the economic advantages.

Stephanie: One observation that has stayed with me from customer projects is that many companies focus almost exclusively on bottlenecks. RTT also makes unused capacity visible. Seeing underutilization alongside bottlenecks often changes the entire discussion and opens up completely new opportunities for improving productivity.

Artificial Intelligence is currently one of the biggest topics in manufacturing. Where do you see the real value of AI in production planning?

Selçuk: For me, one of the greatest opportunities lies in pattern recognition. Instead of manually searching for recurring issues, AI can analyze years of historical data and detect patterns that would be almost impossible to identify otherwise. For example, AI may recognize that a specific packaging material repeatedly becomes critical before seasonal demand peaks. Rather than reacting after the problem occurs, the system can warn planners in advance and highlight potential risks before they impact production. This allows planners to become proactive instead of reactive.

Yasin: I actually believe the greatest value of AI is speed rather than magic forecasting. Forecast accuracy can certainly improve with AI, but the real breakthrough is shortening planning cycles dramatically. Instead of spending days collecting information, running scenarios and interpreting dashboards, planners can simply ask questions in natural language. The system executes the simulation, evaluates the results and explains the recommendations within seconds. That fundamentally changes how planning works. At the same time, we should separate today's reality from the current hype. Fully autonomous planning systems that make business-critical decisions entirely without human supervision are still some way off. The real value today comes from AI acting as an intelligent co-pilot—with a human remaining in control.

Hans: I completely agree. The future lies in semi-autonomous systems. AI can analyze historical data, identify patterns, recognize risks and prepare recommendations. But the final decision remains with the planner. Another exciting development is conversational interaction. Instead of navigating through dashboards and reports, planners will increasingly communicate directly with the planning system, asking questions in their own language and receiving immediate, context-aware answers. That makes advanced planning accessible to many more users throughout the organization.

AI is only as good as the data behind it. What kind of data does good AI actually need—and what happens if data quality isn't perfect?

Selçuk: AI doesn't simply need more data. It needs context. You can provide thousands of product numbers, but without understanding which machines produce those products, which materials they require or how they relate to one another, the information has very little value. Good AI depends on connected data rather than isolated data. Relationships between datasets are what create meaningful intelligence.

Yasin: Perfect data doesn't exist—and fortunately it doesn't have to. What matters is that the critical planning information is reliable. Lead times, lot sizes, minimum order quantities, machine capacities and inventory levels form the foundation for good planning. If these key parameters are inaccurate, even the fastest AI will simply produce incorrect recommendations more quickly. That's why data quality and planning quality must continuously improve together.

Hans: We always encourage customers to improve planning and data quality in parallel. Production data, bills of material and process definitions should be continuously refined while planning quality increases at the same time. These two developments reinforce each other. As planning becomes better, data quality also improves—and vice versa.

People often ask whether AI will eventually replace production planners. How do you see the role of planners evolving?

Yasin: The role changes—but it doesn't disappear.

Selçuk: Today, many planners spend a significant part of their working day collecting data, maintaining spreadsheets and reacting to operational issues. With systems like RTT, those repetitive tasks are largely automated. Instead of acting as data administrators or constantly firefighting, planners become orchestrators. They evaluate scenarios, compare alternatives and focus on strategic decisions that create value for the business. Technology takes over routine work. People concentrate on decision-making.

Hans: Ultimately, planning remains a human responsibility. Technology provides transparency, simulations and recommendations. People contribute experience, business understanding and judgment. The strongest results always come from combining intelligent software with human expertise.

How closely do you work with customers when developing new functionalities?

Yasin: Very closely. Most new features are not developed in isolation but originate directly from real customer situations. Customers provide actual planning scenarios, capacity constraints and operational challenges. We build new functionality around these real-world use cases rather than theoretical specifications. Another important aspect is flexibility. Many planning parameters can be configured directly within RTT, allowing customers to adapt the system without changing the underlying software.

Hans: Every new functionality is validated together with the customer. After development, customers test the feature within their own planning environment and provide feedback before it becomes part of the productive system. This close collaboration ensures that new developments solve practical business problems rather than technical ones.

Looking ahead, what do you think the supply chain of the future will look like?

Selçuk: I believe we are moving towards self-healing supply chains. Imagine a major port closing unexpectedly somewhere in the world. Instead of waiting for someone to detect the issue, future planning systems will recognize the disruption automatically, calculate the consequences, propose alternative supply routes and adjust production plans accordingly. Many of these processes will happen without manual intervention.

Hans: At the same time, transparency and connectivity will continue to increase. Supply chains are becoming more interconnected every year. Industry 4.0, real-time planning and AI are converging into one integrated planning environment where information flows continuously across the entire value chain. That will fundamentally change the speed and quality of decision-making.

If you could give every CEO just one piece of advice, where should they start?

Selçuk: I would start by looking for the hidden spreadsheets. Almost every company still has planning activities taking place outside the official systems. These manual processes often reveal exactly where important information is missing and where the biggest opportunities for improvement exist.

Yasin: My advice would be: don't start with a large transformation programme. Start with one important business decision. Take one planning challenge, solve it using your own data and demonstrate measurable value within a few weeks. Once that proof has been established, scaling becomes much easier.

Hans: And always view manufacturing as one integrated system. Production processes, operational excellence, data quality and digital planning cannot be optimized independently. Only when people, processes and technology work together can companies unlock the full potential of real-time planning.

Finally, what business results can companies realistically expect from moving towards real-time planning and synchronization?

Selçuk: One of the biggest benefits is reducing unnecessary inventory. When companies gain visibility into future demand and capacity, they no longer need to build excessive safety stocks simply to compensate for uncertainty. Better planning creates more confidence—and confidence reduces inventory.

Yasin: Companies also gain a much clearer understanding of the entire planning situation. Instead of reacting to individual problems, they see the complete picture, detect risks earlier and make better decisions across the entire supply chain.

Hans: Particularly in complex manufacturing environments with large product portfolios, companies can significantly reduce inventory while simultaneously maintaining or even improving delivery performance. At first glance, that may seem contradictory. But with real-time planning, discrete simulation and synchronized decision-making, these objectives can be achieved together.

Closing thought

Today's supply chains are becoming increasingly complex.

More products, shorter product lifecycles, global disruptions and growing customer expectations require faster and better decisions than ever before.

Real-time planning, intelligent simulations and AI are transforming production planning from a reactive process into a proactive decision-support system. The goal is not to replace planners. The goal is to give them the transparency, speed and confidence they need to make better decisions every single day.

Because maximum productivity begins with clear decisions.

Questions by Stephanie Stremler, host of the STREMLER podcast Supply Chain & Friends.