It’s 7:00 a.m., and I’m stepping onto the factory floor. Machines are running steady. Teams are getting into rhythm. And there’s a high-priority order that needs to ship by Friday.

 

We’re on track—for now. But I know how fast that can change.

 

I do a quick check-in on Machine RZ92. It’s a key player in today’s output. We’re not behind yet, but it wouldn’t hurt to get a little ahead. I consider bumping up performance slightly—nothing major, just enough to stay comfortable.

 

Now I’ve got two options.

 

Option A: Go with my gut. I’ve made similar adjustments under pressure before, and things have worked out.

 

Option B: Try out the new GenAI-powered operational dashboard that was just rolled out on the floor. It can simulate the impact of changes, draw from past machine data, and help inform the decision.

 

Which should I choose?

 

Path A: Go with your gut and push ahead

I bump Machine RZ92’s performance from 80% to 86%. We’ve done this before in a pinch. It’s not a huge leap and, at first, the results are promising. Output ticks upward, and we’re making solid progress toward our target.

 

But a few hours into the shift, I get a vibration alert. Then a spike in operating temperature. Then ... shutdown.

 

It turns out the increase, though minor, pushed a component just past its limit. Maintenance teams confirm that heat stress has led to a failure. The repair will take the rest of the day.

 

We lose production time, scrap a batch of parts, and put our delivery timeline at risk.

 

Path B: Ask AI before you act

This time, I decide to consult the new dashboard.

 

Me: “What happens if I increase RZ92’s performance from 80% to 86%?”

 

AI Assistant: “That adjustment would increase throughput by 15%. However, based on machine specs and historical performance, operating above 85% for extended periods increases the likelihood of component failure due to thermal load and mechanical stress.”

 

Me: “Is there a safer option?”

 

AI Assistant: “You can temporarily raise output to 84% during peak hours with minimal risk. If additional output is needed, consider reallocating part of the load to Machine RZ88.”

 

The system even surfaces documentation from the machine’s manual with guidelines for load balancing and short-term optimization.

 

I decide to follow the recommendation—adjust output slightly, spread the work, and build in buffer time to keep everything on track. I’m not met with any breakdowns or wasted material; we stay well within schedule and deliver the product to a happy customer on Friday.

 

What GenAI-enhanced dashboards make possible

Traditional dashboards show what’s happening now, but GenAI-enhanced dashboards help answer, “What happens if…?”

 

They analyze performance trends in real time, cross-reference historical data, and simulate the downstream impact of a single change. They don’t just flag issues—they help you understand what’s causing them, and what to do next.

 

Instead of digging through logs or second-guessing a decision, you can simply ask:
 “What’s the best way to increase output without risking downtime?”

 

And the system rapidly responds with a tailored, data-driven answer—backed by operational history and machine-specific context. Essentially, foresight becomes 20/20.

 

You’re no longer just reacting to problems. You’re anticipating them—and making decisions that lead to preventing them in the first place. In a fast-paced production environment where critical decision making is a constant, that kind of clarity makes all the difference.

 

Accelerate smart decision making with Slalom’s GenAI solutions

You can achieve this kind of real-time clarity with Slalom’s GenAI-Enhanced Operational Dashboard Accelerator.

 

Just as GenAI draws from machine data, contextual trends, historical patterns, and subject-matter knowledge to guide decisions—Slalom brings decades of experience working alongside manufacturers to understand the complexity of operations and the cost of getting decisions wrong.

 

We’ve partnered with AWS and Intel to deliver best-in-class GenAI solutions that optimize ROI, accelerate time to value, and reduce implementation costs—so your team can focus on what matters most: making smarter decisions, faster.

 

If you’ve been asking:

• How can GenAI improve real-time decision making in manufacturing?
• Can AI-powered dashboards reduce downtime and prevent machine failure?
• What’s the fastest way to implement GenAI in our operations without disrupting production?

 

We’ve got the information you need. Visit our GenAI Accelerator page to see how our accelerators work, explore real-world manufacturing use cases, and request a demo customized to your use cases, business, or industry. Qualifying customers may also be eligible for funding to support a proof of concept.

 

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