Monday morning meetings are no longer a formality

At exactly 9:00 a.m., the operations director opens the weekly meeting. On the table there are reports, Excel files, a few charts. Volumes are stable, deliveries are on track, complaints are under control. And yet, margins have dropped again. No one can say exactly why. Some mention overtime, others a few more urgent requests, others increasingly demanding customers. All plausible explanations, but none verifiable at that moment. The data exists, but it arrives late, or it does not arrive together.

Figures from the Contract Logistics Observatory help explain why this scene is happening more and more often. Real market growth is around +0.3%, while labor costs are increasing by +4.4%. This means that even a company that is “working well” can see its margins erode without clear warning signs. No crisis is needed, just a series of micro-decisions made without a clear understanding of their economic impact.

Looking toward 2026, the real risk is not working less, but working blind. In this context, Business Intelligence is not meant to prove what happened, but to understand what is happening while it is happening.

When complexity increases, data starts to contradict itself

After growth through acquisitions, the organization is larger, but not yet unified. Each warehouse has kept its own tools, each transport office its own habits. Definitions sound the same, but they are not truly aligned. “Order fulfilled”, “on-time delivery”, and “productivity” change slightly from one site to another. No one does it on purpose, it just happens. The problem emerges when those numbers need to be consolidated at management level.

Industry consolidation, with dozens of acquisition and merger operations every year, is multiplying this situation. More structures mean more data, but also more versions of the truth. The result is that meetings start by talking about numbers and end by talking about numbers, without reaching decisions. Operational Business Intelligence is born exactly here, not to add another reporting layer, but to create a shared language. When data is not comparable, complexity grows faster than the ability to manage it. And toward 2026, this asymmetry will become one of the main brakes on sustainable growth.

AI enters the scene when uncertainty becomes too expensive

When people talk about Artificial Intelligence, the most common idea is that of a system that makes decisions instead of people. In real operational contexts, the opposite happens. AI is adopted when people have to decide too often, with too many variables and too little time.

It is no coincidence that today AI is mainly applied to order management and demand forecasting, both accounting for 14% of use cases. Here, mistakes are not abstract. They mean wrong shifts, underutilized vehicles, missed delivery windows.

The Observatory shows that 81% of companies that have adopted AI solutions report concrete benefits, and only 11% talk about replacing human labor. The interesting point is this. AI does not eliminate decision responsibility, it eliminates noise. It reduces unnecessary variables, highlights recurring patterns, and makes anomalies visible that would otherwise emerge too late. Toward 2026, AI will not be a differentiating element to talk about, but a silent component of everyday Business Intelligence. It will not make headlines, but it will make the difference.

The moment when data stops being numbers and becomes choices

At the end of the month, when final reports arrive, it is already too late to correct many decisions. Cost per order has increased, but shipments have already left. A customer is eroding margins, but service has been guaranteed for weeks without clear warning signs. This is where the limit of a BI designed only to look backward becomes evident.

With energy costs rising and margins under pressure, deciding late means losing value. Operational Business Intelligence exists for this reason, to make data readable while processes are still running. Not to control, but to choose. Knowing today that a route is going out of control, knowing now that a line is losing efficiency, knowing immediately where to intervene. Toward 2026, the most mature companies will no longer ask what data they have available, but which decisions they can make right now. At that point, BI and AI stop being tools and become part of the way of working.