Published on August 21, 2026<\/p>\n<\/div>
A company can have too much substance \u2013 and at the same time too little of what it really needs.<\/p>\n
That sounds paradoxical. In practice, I encounter this exact situation time and again: Warehouses are full, a lot of capital is tied up, and yet the very parts that are crucial for production or customer orders are missing.<\/p>\n
That was exactly the case in one of our projects.<\/p>\n
At first glance, it looked like a problem with the inventory. However, closer analysis revealed that the real problem was not the quantity of material, but its composition.<\/p>\n
Simply put:
\nIt wasn't that there was too little in stock. The wrong thing was in stock.<\/b><\/p>\n
And incorrect forecasts aren't always to blame. Sometimes sales, purchasing, production, and supply chain make perfectly reasonable decisions individually \u2013 and yet together they still create the wrong amount of inventory.<\/p>\n<\/div><\/div><\/div><\/div><\/div>
The inventory paradox<\/h3><\/div><\/div><\/div>High inventory levels are often equated with security of supply. However, the total quantity of stock says little about whether a company is actually able to deliver.<\/p>\n
The crucial factor is whether the right parts are available at the right time.<\/p>\n
This is precisely where the inventory paradox arises: companies tie up considerable financial resources in their warehouses and at the same time have to deal with missing parts, production interruptions or delivery problems.<\/p>\n
You end up paying twice: for too much stock and for insufficient availability.<\/b><\/p>\n<\/div><\/div><\/div>![](\"https:\/\/emarticon.de\/wp-content\/uploads\/6-Impuls-Foto.png\")
<\/span><\/div><\/div><\/div><\/div><\/div>For me, this is an important warning sign. Because the cause often lies not in the warehouse itself, but much earlier in the management of the supply chain.<\/p>\n
Therefore, in our project we first had to understand how the stock had come about in the first place.<\/p>\n
\n- How reliable were the demand forecasts?<\/li>\n
- How were the warehouses managed for different items and demand patterns?<\/li>\n
- How quickly were discrepancies between planning and actual demand identified?<\/li>\n
- Were responsibilities clearly defined?<\/li>\n
- And did processes and incentive systems actually lead to decisions that were beneficial for the company as a whole?<\/li>\n<\/ul>\n
This revealed an insight that I see confirmed time and again in many projects:<\/p>\n
Ultimately, what exists is the visible result of many decisions that were made long before.<\/b><\/p>\n
Inaccurate forecasting can lead to overstocking. Undifferentiated inventory management can result in non-critical products being overstocked, while critical parts are not adequately protected. Slow decision-making processes can prevent timely responses to changing demand.<\/p>\n
Things get particularly tricky when each department optimizes according to its own goals. Sales, for example, works towards sales and revenue targets \u2013 and a bonus might be tied to them. Purchasing pursues cost and terms targets, production wants to make its processes as efficient as possible, and the supply chain wants to ensure high availability.<\/p>\n
Each individual decision can be plausible from the perspective of its respective area.<\/p>\n
However, this interaction can still result in both overstocking and shortages.<\/p>\n
That is precisely why such a problem can rarely be solved by logistics alone.<\/b><\/p>\n<\/div><\/div><\/div>Four levers for better inventory management<\/h3><\/div>In our project, we considered several levels simultaneously: demand forecasting, processes, software, SKU management, and organizational responsibilities.<\/p>\n
For me, four key levers can be derived from this:<\/b><\/p>\n
1. Better understand the need<\/b><\/p>\n
No forecast will perfectly predict the future. However, companies need to be able to identify where demand is stable, where it fluctuates significantly, and for which products forecast errors will be particularly costly.<\/b><\/p>\n
2. Differentiated control of articles<\/b><\/p>\n
Not every part requires the same inventory logic. Value, criticality, lead time, procurement risk, and consumption patterns must all be considered. A readily available standard part requires a different management approach than a critical component with a long replenishment lead time.<\/b><\/p>\n
3. Detect deviations early<\/b><\/p>\n
Crucial is not only the quality of the planning, but also the speed of reaction. If forecasts and actual demand diverge, it must be clear who recognizes the discrepancy, who decides, and what measures follow.<\/b><\/p>\n
4. Steer towards the overall optimum<\/b><\/p>\n
Key performance indicators, responsibilities and incentive systems must be designed in such a way that individual departments do not optimize their targets while the overall result for the company deteriorates.<\/p>\n
It is precisely here, in the fourth point, that I believe an often underestimated lever lies. If each department is successful on its own, but the company as a whole ties up more capital and is still unable to deliver, the problem often lies not in the individual decision \u2013 but in the underlying management logic.<\/p>\n
Technology can provide support. Modern planning systems and artificial intelligence can recognize patterns, improve forecasts, and make deviations visible earlier.<\/p>\n
However, they do not replace a clear control logic.
\nTherefore, the crucial question is not: Which software do we need?
\nBut rather: What decisions do we want to make with better data?<\/strong><\/p>\n<\/div><\/div><\/div>What companies can learn from this<\/h3><\/div>For me, that's precisely where the change in perspective lies:<\/p>\n
Security of supply is not achieved by stockpiling as much material as possible. It is achieved by... <\/b>Companies with regard to <\/b>To deliberately manage uncertainty.<\/b><\/p>\n\n- Which parts are truly critical?<\/li>\n
- Which risks do we want to hedge against with existing assets?<\/li>\n
- How much stock is required for that?<\/li>\n
- And where are we storing materials without creating any corresponding benefit?<\/li>\n
- How do we distribute the responsibility for this?<\/li>\n<\/ul>\n
Those who can answer these questions do not have to choose between low stock levels and high supply security.<\/p>\n
Good supply chain management must achieve both simultaneously.<\/b><\/p>\n
Therefore, if high inventory levels and missing parts occur simultaneously, I would not first look at the absolute inventory, but at the inventory ranges of individual product groups \u2013 differentiated according to criticality and demand volatility.<\/p>\n
Where this relationship does not seem plausible, I would take a closer look and ask:
\nWhat decisions led to this situation?<\/p>\n
Because a full warehouse can mean security of supply.
\nHowever, it can just as easily be an indication that a company is unnecessarily compensating for uncertainty with capital.<\/p>\n<\/div>
Therefore, the crucial question for me is:<\/h2>\nDo you know which specific risk you are hedging against with your key assets?<\/b><\/p>\n
If there is no clear answer to that, it's worth looking behind the scenes. <\/b>the total inventory.<\/b><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>\ud83d\udc49<\/b> <\/b>More on this topic:
\nHow Emarticon helps companies combine security of supply and efficiency in supply chain management:<\/p>\n
\u2192 Interim supply chain management<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div>
High inventory levels are often equated with security of supply. However, the total quantity of stock says little about whether a company is actually able to deliver.<\/p>\n
The crucial factor is whether the right parts are available at the right time.<\/p>\n
This is precisely where the inventory paradox arises: companies tie up considerable financial resources in their warehouses and at the same time have to deal with missing parts, production interruptions or delivery problems.<\/p>\n
You end up paying twice: for too much stock and for insufficient availability.<\/b><\/p>\n<\/div><\/div><\/div> For me, this is an important warning sign. Because the cause often lies not in the warehouse itself, but much earlier in the management of the supply chain.<\/p>\n Therefore, in our project we first had to understand how the stock had come about in the first place.<\/p>\n This revealed an insight that I see confirmed time and again in many projects:<\/p>\n Ultimately, what exists is the visible result of many decisions that were made long before.<\/b><\/p>\n Inaccurate forecasting can lead to overstocking. Undifferentiated inventory management can result in non-critical products being overstocked, while critical parts are not adequately protected. Slow decision-making processes can prevent timely responses to changing demand.<\/p>\n Things get particularly tricky when each department optimizes according to its own goals. Sales, for example, works towards sales and revenue targets \u2013 and a bonus might be tied to them. Purchasing pursues cost and terms targets, production wants to make its processes as efficient as possible, and the supply chain wants to ensure high availability.<\/p>\n Each individual decision can be plausible from the perspective of its respective area.<\/p>\n However, this interaction can still result in both overstocking and shortages.<\/p>\n That is precisely why such a problem can rarely be solved by logistics alone.<\/b><\/p>\n<\/div><\/div><\/div> In our project, we considered several levels simultaneously: demand forecasting, processes, software, SKU management, and organizational responsibilities.<\/p>\n For me, four key levers can be derived from this:<\/b><\/p>\n 1. Better understand the need<\/b><\/p>\n No forecast will perfectly predict the future. However, companies need to be able to identify where demand is stable, where it fluctuates significantly, and for which products forecast errors will be particularly costly.<\/b><\/p>\n 2. Differentiated control of articles<\/b><\/p>\n Not every part requires the same inventory logic. Value, criticality, lead time, procurement risk, and consumption patterns must all be considered. A readily available standard part requires a different management approach than a critical component with a long replenishment lead time.<\/b><\/p>\n 3. Detect deviations early<\/b><\/p>\n Crucial is not only the quality of the planning, but also the speed of reaction. If forecasts and actual demand diverge, it must be clear who recognizes the discrepancy, who decides, and what measures follow.<\/b><\/p>\n 4. Steer towards the overall optimum<\/b><\/p>\n Key performance indicators, responsibilities and incentive systems must be designed in such a way that individual departments do not optimize their targets while the overall result for the company deteriorates.<\/p>\n It is precisely here, in the fourth point, that I believe an often underestimated lever lies. If each department is successful on its own, but the company as a whole ties up more capital and is still unable to deliver, the problem often lies not in the individual decision \u2013 but in the underlying management logic.<\/p>\n Technology can provide support. Modern planning systems and artificial intelligence can recognize patterns, improve forecasts, and make deviations visible earlier.<\/p>\n However, they do not replace a clear control logic. For me, that's precisely where the change in perspective lies:<\/p>\n Security of supply is not achieved by stockpiling as much material as possible. It is achieved by... <\/b>Companies with regard to <\/b>To deliberately manage uncertainty.<\/b><\/p>\n Those who can answer these questions do not have to choose between low stock levels and high supply security.<\/p>\n Good supply chain management must achieve both simultaneously.<\/b><\/p>\n Therefore, if high inventory levels and missing parts occur simultaneously, I would not first look at the absolute inventory, but at the inventory ranges of individual product groups \u2013 differentiated according to criticality and demand volatility.<\/p>\n Where this relationship does not seem plausible, I would take a closer look and ask: Because a full warehouse can mean security of supply. Do you know which specific risk you are hedging against with your key assets?<\/b><\/p>\n If there is no clear answer to that, it's worth looking behind the scenes. <\/b>the total inventory.<\/b><\/p>\n<\/div> \ud83d\udc49<\/b> <\/b>More on this topic: \u2192 Interim supply chain management<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/span>\n
Four levers for better inventory management<\/h3><\/div>
\nTherefore, the crucial question is not: Which software do we need?
\nBut rather: What decisions do we want to make with better data?<\/strong><\/p>\n<\/div><\/div><\/div>What companies can learn from this<\/h3><\/div>
\n
\nWhat decisions led to this situation?<\/p>\n
\nHowever, it can just as easily be an indication that a company is unnecessarily compensating for uncertainty with capital.<\/p>\n<\/div>Therefore, the crucial question for me is:<\/h2>
\nHow Emarticon helps companies combine security of supply and efficiency in supply chain management:<\/p>\n