Elisabetta Villa

The 6 KPIs That Actually Tell You If Your Logistics Are Under Control

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In most logistics companies today, data is not missing.
What is missing is silence and priority.

Dashboards, reports, indicators, weekly, monthly and yearly comparisons. Every function measures something. Every piece of software promises visibility. Every meeting brings a new number to the table. The result is paradoxical. The more KPIs there are, the less useful they become for decision making.

This happens because in logistics data is often added, rarely chosen.
What gets measured is what is easy to extract, not what truly governs the system. The outcome is dozens of disconnected indicators, read after the fact, useful to explain what already happened but weak when it comes to anticipating what is about to happen.

Key operational logistics KPIs

The problem is not technical. It is cognitive.
When everything looks important, nothing really is. Weak signals get lost in the noise, priorities blur, and decisions always arrive one step after the operational effect.

In this context, adding new KPIs does not improve control.
Often, it makes it worse.

Logistics does not need more numbers. It needs a few right indicators, capable of describing the real state of the system before a problem becomes visible to everyone. Indicators that bring order, not complexity.

This is where the right question comes from, the one almost nobody asks.
If you had to choose only a few, which KPIs actually matter?

In logistics, a few indicators drive everything else

A warehouse does not work as a sum of independent activities.
It works as a system.

Inbound, storage, picking and outbound are not separate blocks you can optimize one by one. They are interconnected parts, where every imbalance quickly propagates to the others. When something goes wrong, the effect is always visible downstream, but the cause is almost always upstream.

This is where many measurement systems fail.
They focus on where the problem explodes, not where it originates.

A slowdown in picking is almost never just a productivity issue. It is often the result of irregular inbound, growing saturation or unbalanced inventory. A declining service level rarely depends only on outbound. It is the final point of a chain of decisions made days or weeks earlier.

That is why not all logistics KPIs carry the same weight.
Some indicators describe local symptoms. Others tell the story of the entire system.

The truly relevant KPIs are those that allow you to understand whether the warehouse is working in balance or constantly compensating. Whether it is absorbing variability in a healthy way or accumulating operational tension.

When these indicators hold, everything else is manageable.
When they break, even the most “good looking” KPIs stop making sense.

This is why it makes sense to talk about a small set of key KPIs. Not because the others are wrong, but because without a clear hierarchy the risk is measuring everything and controlling very little.

The 6 KPIs that describe the real behavior of logistics

If you look at a logistics system from above, without diving into operational details, the same balance points always emerge. These are what determine whether a warehouse runs smoothly or spends the day chasing problems.

They do not depend on the industry, order volume or layout complexity.
They depend on how flows behave.

There are six of them.

Inbound performance
Because most logistics problems do not start where they explode, but in how goods enter the system. Irregular inbound creates instability before the warehouse even realizes it.

Key operational logistics KPIs
Key operational logistics KPIs

Warehouse saturation
Space is not just a physical constraint. It is a decision margin. When saturation grows without control, every activity becomes more expensive, even if volumes appear stable.

Inventory and rotation
Stock is never neutral. Some inventory works for the business. Some silently slows it down. Understanding how and where goods accumulate is essential to avoid structural inefficiencies.

Picking productivity
Picking is where all inefficiencies become visible. Measuring it is not about finding someone to blame, but about understanding where the system creates operational friction.

ABC analysis
In every warehouse, a small number of items generates most of the work. Ignoring them means optimizing marginal details while leaving the real workload untouched.

Key operational logistics KPIs

Outbound and service level
This is the final point of the system. It shows whether the promises made to customers are sustainable or whether the warehouse is simply catching up late.

These six KPIs do not explain every single activity.
They explain whether the logistics system, as a whole, is working in balance or in constant compensation.

If only one of them is out of control, the warehouse can still function.
If more than one starts sending signals, the problems are not episodic. They are structural.

The same KPIs, three roles, one shared advantage

One of the most common misunderstandings about logistics KPIs is thinking they are only for people who “do analysis”. In reality, the same indicators take on different meanings depending on who reads them.

The same six KPIs can support operational, managerial or executive decisions, without changing the numbers, only the perspective.

People on the floor use them to anticipate issues, prepare work and reduce daily urgency.
Warehouse managers use them to understand whether processes, layout and organization are coping with real variability.
Operations and supply chain leaders use them to connect logistics, costs and service level, and decide where to intervene and where to invest.

It is the same set of KPIs, read on three different levels.

This is exactly why the manual is not designed for a single profile, but for anyone who holds responsibility over logistics, from operations to executive level. It does not explain how to build indicators, but which ones truly matter and why.

If you want a clear view of the 6 fundamental logistics KPIs and understand how to read them based on your role,

When BI stops being an IT project and becomes an operational tool

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The scene is almost always the same.
The data is there—it comes from the WMS, the TMS, the ERP, and from Excel files no one dares to touch anymore.
Someone has even built dashboards—maybe nice to look at—but when a real answer is needed, that answer doesn’t arrive. Or it arrives too late.

Business Intelligence stays there, locked inside a technical perimeter, managed by IT or an external consultant, far from the people who have to make decisions every day.
The logistics manager looks at the numbers but can’t immediately understand where the problem is. Transport costs increase, but it’s not clear why. The warehouse slows down, but the charts don’t tell the story.

At that point, BI stops being a working tool and becomes just another IT project—technically correct, but disconnected from real operations.

The problem isn’t the data, but how it’s turned into charts

This is where the real issue emerges.
Data is not missing—if anything, there’s too much of it.
The problem is that it’s turned into charts designed for the people who build them, not for those who need to read them.

Crowded histograms, endless tables, KPIs all treated the same way, colors that don’t help distinguish what matters from what’s just noise.
The result is paradoxical: the more numbers there are, the less clarity you get.

People working in logistics and transport aren’t looking for elegant reports. They’re looking for fast answers.
Where am I losing time? Where am I overspending? What has changed compared to last week?

When charts don’t help answer these questions, BI stops guiding decisions and turns into a simple reporting exercise.

When BI becomes an operational tool

The turning point comes when Business Intelligence stops being built around data and starts being built around decisions.

Dashboards are no longer designed to show everything, but to immediately highlight what really matters in logistics and transport.

A few key indicators, readable at a glance, designed for day-to-day operations: order fulfillment times, transport costs, warehouse saturation, delivery punctuality.

Numbers that speak the language of people working in the field.

At this point, BI becomes a real working tool again—not a one-off project.
Dashboards are opened every day, not just at the end of the month, because they help understand what’s happening and where to act immediately.

This is where data visualization stops being aesthetic and becomes functional.

The creator user as a driver of autonomy

The real leap forward happens when BI no longer depends on someone who “builds the charts,” but on those who know the processes.

With the creator user, the platform isn’t just used to view predefined data—it allows dashboards to be expanded and adapted autonomously.
No code to write. No tickets to open. No weeks of waiting.

Those managing logistics and transport can add a view, drill into an anomaly, cross different datasets the moment a question arises.
BI becomes as flexible as the business it supports.

It’s no longer an advanced feature reserved for specialists—it’s an operational tool that grows with the company.
And that’s when data stops being just numbers and truly starts driving decisions.

What is BI and why a supply chain needs Business Intelligence

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Imagine a warehouse manager starting the day with three windows open on their screen: the Excel file with stock levels, the ERP dashboard, and a monthly report that arrived last night from the administration department.
Three worlds that don’t talk to each other, three different versions of the same reality.
He needs to understand whether there is actually enough space today to receive the incoming load from the Asian supplier or whether production is at risk of stopping.
He looks around, sighs, and does what everyone does in these situations: he makes a guess.

Why logistics needs BI

It’s a recurring scene. In warehouses, transport offices, supply chain departments.
There is no shortage of data—if anything, there is too much. What’s missing is a way to make it all communicate, to turn “numbers” into a readable story.
In those moments, the supply chain resembles a dashboard with all warning lights on… but without labels. Something is happening, but you don’t know what.
And so companies drift toward “intuitive management,” based on experience and memory.
It works as long as the market is stable—until unexpected peaks arrive, customers become more demanding, or transport costs spiral out of control.

Why generic BI tools are no longer enough in complex sectors

At some point, almost every company follows the same path.
They buy a general-purpose BI platform, start the project with enthusiasm, configure a few dashboards—and for a while, it works. Then comes the moment when logistics reality knocks on the door with hands dirty from day-to-day operations.
And that’s when the magic fades. The Logistics Manager wants to understand why saturation shot up to 85% last month, but the BI offers a pie chart that looks like it came from a school textbook. The Transport Manager requests a comparison of costs by route, carrier, and average shipped weight—what he gets is a perfect dashboard… except that no one has ever configured the calculation logic typical of transport.

The Supply Chain Director wants to see profitability per customer, including actual logistics costs, not the “estimated” ones—and discovers that the platform can’t do it without months of development.

Why logistics needs BI

The problem isn’t technology. General BI tools are excellent platforms—but they don’t know the industry. For them, a pallet is a “record,” a shipment is a “table row,” saturation is a “derived metric.” But in logistics and transport, every piece of data has a precise operational meaning. If you don’t teach it, it won’t understand it. And teaching it costs time, energy, and budget most companies don’t have.
The result? Everyone starts from scratch. Each company builds its own version of logistics KPIs, its own cost formulas, its own filters and dashboards. It’s like asking every restaurant to grow its own wheat just to have flour. Possible, yes. Logical, no.

Because the speed at which a company turns data into decisions doesn’t depend on how many dashboards it has—
but on how well those dashboards speak its language.

A vertical BI that speaks the language of logistics

Then something simple but decisive happens. Someone turns on a BI system that already comes with the vocabulary of logistics and transport built in. You no longer need to explain to a consultant what saturation is, or how the true average transport cost per customer is calculated. You no longer need to invent KPIs, filters, or formulas from scratch. You open a tool that instantly understands your world—because it was designed for it. And the difference is immediate. A Logistics Manager opens the dashboard and sees a map of space waste, updated daily, showing which items are consuming capacity without generating value.
He no longer needs to guess where to look—the BI shows it.

Why logistics needs BI

A Transport Manager finally gets a serious performance comparison between carriers, complete with punctuality, costs, vehicle saturation, SLA compliance.
Instead of generic charts, he has a picture that allows him to negotiate contracts with real arguments—not impressions.

A vertical BI does exactly this:
it shortens the distance between data and decision.
It doesn’t force you to build the structure—it gives it to you, ready-made, tested, and meaningful.

And this creates something far more valuable than technology: trust.
When a dashboard is built on KPIs that professionals recognize, they use it.
They browse it.
They build meetings around it.
They make decisions with it.

A generic BI tool asks you to adapt to it.
A vertical BI adapts to your way of working.

At that point, logistics stops being a puzzle to solve at the end of each month and becomes a system you can read in real time.
This is where industry-specific BI becomes a competitive lever—because it gives time, clarity, and speed to those steering the company through a supply chain that waits for no one.

This is the moment when BI stops being software.
It becomes an advantage.
And the companies that adopt it don’t just “look at data”—
they understand it.
And when you understand data, you finally start changing the game.

Why move from Excel to a BI system built for your supply chain

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At first, everything seems under control. One sheet for inbound, one for shipments, one for transport costs. Three files—no panic.
Then a new client arrives, a promotion starts, a colleague updates the “final” file with a version called “final_v2,” and within a few months your desktop looks like the secret archive of a data archaeologist.
Every morning starts with the hunt for the right file. You remember updating the picking column, but you’re not sure whether you did it on the server, your desktop, or the copy you emailed yourself “just in case.”
Meanwhile, someone else opens another version, makes a small change (nothing major—just a formula), and within a week, the numbers no longer match.

BI alternativa a Excel logistica

Excel was made for calculations, not for managing an entire data ecosystem.
And when your supply chain grows—with hundreds of shipments, warehouses, suppliers, and customers—the spreadsheet turns into a jungle.
The more data you add, the slower the formulas get.
The more people collaborate, the faster consistency breaks.
Until one day you realize that total stock in Excel doesn’t match your ERP—and you have no idea why.

While you’re trying to figure it out, someone asks for an urgent report.
You export, clean, and send it… only to realize you worked on the wrong version.
At that point, it’s no longer a spreadsheet. It’s a trap.

What you lose by staying on Excel

With Excel, you can do a lot—but you can’t see everything.
It’s like trying to look at your entire supply chain through a keyhole.
You see one piece, then another, but never the full picture.
Want to know how much time passes between receiving and shipping an item?
You’ll need to filter, copy, paste, tweak a pivot table, and hope no one has changed the date format. Want to calculate the average vehicle saturation over the last quarter?
Make some coffee—you’ll need it.

Excel tells you what happened, but not why. It shows you a number, but not the trend behind it. And when your data comes from multiple systems—warehouse, transport, administration—errors and inconsistencies are inevitable.

BI alternativa a Excel logistica

With a BI solution built for the supply chain, instead, you see everything in real time.
Dashboards immediately show where costs pile up, where minutes are lost, where the flow gets stuck.
No more searching through spreadsheets—just one click or a question to the AI like:
“How many days was stock above the average?”
and you get the answer—graph included.
Excel forces you to chase data. BI makes the data work for you.

When BI changes your day (and the way you decide)

The first sign that something has changed is silence.
No more “Can you send me the updated file?”
No more email chains checking who has the latest version.
You open your dashboard, see real-time KPIs, and can finally drink your coffee without opening ten windows.

With B-AI Semplice, every decision starts from a clear picture of reality.
No more deciphering tables or fighting with filters and formulas.
You already have the metrics that matter—vehicle saturation, delivery punctuality, warehouse productivity, customer costs—all in one dashboard, ready to read.

And when you need a deeper look, just ask. Literally.
The integrated AI answers in natural language:
“Show me the trend of delayed deliveries over the last month” or
“Compare transport costs between Bologna and Milan.”
Within seconds, you have a clear, visual, intuitive answer.

The best part is, you don’t need to change the way you work—just the way you look at your data.
From reactive to proactive.
From “let’s fix the error” to “let’s anticipate the problem.”

In the end, switching from Excel to a tailored BI solution isn’t just a technological choice.
It’s a choice for peace of mind.

When logistics meets data intelligence

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Being a guest at a GEP Informatica webinar isn’t just about visibility.
It’s about meeting the people who, every day, deal with pallets, shipments, deadlines, and ever-tighter margins.

On November 7, we took part in the webinar dedicated to Business Intelligence and Artificial Intelligence for logistics — and the energy in the room confirmed that the sector is ready to take a real step forward.

Dozens of live questions, hundreds of participants, and almost total engagement.

Not because AI is trendy, but because everyone — from Logistics Managers to Transport Directors — is looking for practical answers: how to reduce overstock, anticipate transport delays, and identify where margins are being lost.

Optimize logistics with data

During the session, we showcased B-AI Semplice, the Business Intelligence platform built for those who live and breathe logistics.
You don’t need to speak the language of data — you just need to ask.
“Which customers have the lowest turnover?”
“Where am I spending the most on transport?”
The AI responds with clear, immediate graphs and dashboards — without even opening Excel.

This isn’t theory. It’s everyday practice.
It’s the difference between knowing something’s wrong and instantly knowing where to act.

That’s why we wanted to be there — because simplicity, in both data and processes, is our way of changing the rules of the game.

👉 Watch the full webinar below

The problem isn’t BI. It’s where you start.

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When a company decides to adopt Business Intelligence software, expectations are high—but projects often struggle to take off.
The reason isn’t the technology. It’s the starting point.

Many BI tools are empty shells. Powerful, yes—but empty. Faced with a blank dashboard to fill from scratch, even well-structured companies get stuck.
No one knows where to begin, which KPIs to choose, or which data to activate first.

You need a consultant, an IT team, weeks of integration. And so, the project drags on, slows down—or worse, stops altogether.

B-AI Semplice was created precisely to overcome this block.
It’s the first ready-to-use vertical Business Intelligence platform designed for logistics.
No blank sheets. No development from scratch.
Preconfigured dashboards, field-tested KPIs, and integrated artificial intelligence that lets you ask questions in natural language and get clear, visual, and immediately actionable answers.

You can ask:

  • Which customer has the highest profitability?
  • What’s the saturation level of your vehicles?
  • How much stock has left a specific warehouse in the past 30 days?

And if your data isn’t yet integrated with your ERP or WMS? No problem.
You can start even with a simple Excel file. The data is recognized, organized, and made available right away.

Behind the platform is the expertise of GEP Informatica, a company that has spent years working inside warehouses and operational flows—not in labs.

Everything you see in B-AI Semplice comes from real needs, encountered in hundreds of projects.
It’s designed for people who make decisions every day—under pressure, with little time and a lot of responsibility.

That’s why the impact is immediate. Because you don’t have to wait months to see something that works.
You start right away, customize as you go, and above all, stop wasting time reinventing what already exists.

In logistics, complexity is inevitable. But analysis doesn’t have to be.

With B-AI Semplice, Business Intelligence is no longer a project to plan.
It’s an ally to use. Now.