Process optimization in logistics for SMEs: The most important levers from practice

Most logistics problems in SMEs are not obvious – they are systemic.

What looks like an inventory issue is often a planning issue.
What is discussed as an efficiency problem is, in reality, an interface problem.

And that is exactly why many measures fail to deliver results.

Especially in times of global crises – from disrupted supply chains and volatile demand to geopolitical tensions – these weaknesses become visible. Systems that have “somehow worked” for years suddenly come under pressure.

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When inventory levels rise, the default reaction is almost always to adjust parameters.

But the better question is:
Where in the system is uncertainty being absorbed?

A typical observation from projects:
One area increases inventory because another area does not deliver reliably.

This creates a silent cycle:

Planning becomes less accurate
Operational interventions increase
Trust continues to decline

Especially in volatile times, this effect intensifies. Inventory is no longer actively managed, but rather “built out of fear.”

The real leverage is not in the inventory itself, but at the point where planning is consistently breaking down.

Most SMEs are functionally organized – but not process-driven.

This creates a paradox:
Each department is doing things “right” – yet the overall system doesn’t work.

In stable market conditions, this can often be compensated.
In times of crisis, however, these interfaces are the first to break.

A simple but rarely asked question is:
Who actually decides on priorities in day-to-day operations?

If the answer is “everyone, to some extent,” the system inevitably becomes unstable.

A clearly defined prioritization system has a stronger impact under uncertainty than any detailed optimization.

Many production and logistics systems are optimized for maximum utilization.

The consequences are usually the same:

• Rising work-in-progress
• Longer lead times
• Declining delivery reliability

In stable times, this is less noticeable.
Under fluctuating demand, it becomes a problem.

The key question is:
How much slack does the system deliberately allow to remain stable?

In practice, it often turns out that these “buffers” make the difference – not maximum utilization.

In many SMEs, investments are made when problems become visible.

The uncomfortable reality is:
Many of these problems are recreated every day – through inconsistent planning.

Typical symptoms:

• Frequent shifts in priorities
• Constant rush orders
• Operational firefighting replacing planning

In a volatile environment, these patterns intensify. Planning is increasingly replaced by short-term reactions.

A key lever is not to refine planning further, but to consistently reduce the number of plan changes.

Excel works surprisingly well for a long time – because it is flexible.

But this very flexibility often replaces missing structure.

In stable environments, this can be compensated.
In times of crisis, it becomes critical because transparency and responsiveness are lacking.

The key question before introducing any tool is:
Which decisions should be system-supported in the future – and which should deliberately no longer be made manually?

In practice, it repeatedly becomes clear that progress does not come from major initiatives, but from clarifying fundamental questions: Who decides what, which rules actually apply in day-to-day operations, and where is planning systematically deviated from?

Especially in uncertain times, it becomes visible how robust a system really is.

Often, it is enough to consistently make these points transparent to achieve the first noticeable improvements.

Logistics cannot be optimized in isolation – it must be understood as a system.

In times of global crises, it becomes clear which structures are resilient and which only work under stable conditions.

The real progress happens where companies begin to question their own management systems and consciously change operational patterns.

The key question is not where efficiency can be increased,
but whether the system is managed in a way that works under uncertainty.