Saint-Gobain Weber needed a way to reduce time spent analyzing issues and keep the process aligned with current conditions during production.
By changing how processes are run under changing conditions, they removed the delay between what was happening and how the process was run — improving efficiency, reducing waste, and scaling performance across sites.
Key outcomes
- 90% reduction in problem-solving time for engineering teams
- Reduced material waste through more precise process control
- Deployment across 9 production sites
- Improved production economics through more stable, controlled operations
When Problem Solving Can’t Keep Up
As Saint-Gobain Weber’s operations grew, so did the complexity of managing performance.
Materials didn’t behave the same way from one run to the next. Conditions shifted. And small deviations required constant attention.
Teams were already working to improve performance within their plants. But those improvements didn’t always carry over from one site to another — and they didn’t always hold over time.
As a result, engineers spent significant time investigating issues. Operators relied on experience to make adjustments. And process improvements often came after performance had already drifted.
At this pace, problem-solving couldn’t keep up with production — and performance suffered as a result.
From Data Overload to Delayed Action
Weber teams had no shortage of data. What they lacked was a way to act on it quickly.
Engineers pulled data from multiple systems and spent hours — sometimes entire shifts — trying to understand what had happened.
Even when the root cause was identified, the process had already moved on.
In the bagging process specifically, this led to conservative overfilling to ensure compliance — increasing material usage and cost.
The challenge wasn’t access to information. It was the time required to keep the process aligned as conditions changed.
Acting in the Moment, Not After the Fact
To address this, Weber introduced a new way of running the process — one that adapts in real time as conditions change.
Instead of relying on manual analysis or fixed settings, teams began adjusting the process based on what was happening during production.
The process stayed aligned with the variables that mattered under current conditions — without waiting for analysis hours later.
This shifted how teams operate — from spending hours analyzing issues to keeping the process aligned in the moment.
In the bagging process, this meant moving away from conservative overfilling.
Operators could maintain compliance while minimizing material use, without waiting for engineering analysis.
Engineers no longer needed to manually investigate every deviation.
From Reactive Work to Continuous Improvement
This shift fundamentally changed how Weber teams use their time.
Operators adjust the process based on current conditions instead of relying on experience alone.
Engineers spend less time troubleshooting and more time improving performance.
What once took hours — or entire shifts — now happens in the moment.
Variability didn’t go away. But it no longer slows teams down.
Results
By keeping processes aligned with current conditions during production with Real-Time Process Optimization, Weber achieved measurable operational and financial impact:
90% reduction in problem-solving time
Engineers spend significantly less time investigating issues, freeing capacity for higher-value work
Reduced material waste
More precise control of operating conditions reduced overfilling and improved cost per unit produced
Deployment across 9 plants
What began as a targeted improvement became a repeatable model across the network
Saint-Gobain Weber operators shifted from reacting to issues to continuously keeping the process fully optimized as conditions evolve.
Scaling the Transformation
Following initial success, Weber expanded this approach across its production network.
Today, nine plants use this model to continuously improve performance.
What began as a way to reduce problem-solving time became a scalable way of running operations.
Performance is no longer limited by how quickly teams can analyze the past. It becomes repeatable, transferable, and continuously improving across sites.
Variability didn’t go away. Teams just changed how they operate — acting in the moment instead of spending hours reacting after the fact.
