Manufacturers everywhere are facing a growing challenge: the rapid loss of manufacturing tribal knowledge, the unwritten, experience-driven expertise that has quietly kept factories running for decades.

It’s the technician who can recognize a problem by sound alone.
The engineer who knows why one line behaves differently on Mondays.
The operator who understands the “real way” a process works versus what’s documented.

For years, factories relied on this human know-how to deliver throughput, quality, and uptime.

But today, the equation has changed.

Experienced experts are retiring faster than new workers can be trained. Production lines are more complex. And the cost of losing tribal knowledge is no longer measured in minor inconveniences; it’s measured in hours of downtime, missed customer commitments, and delayed shipments.

This shift is forcing manufacturers to rethink how expertise is captured, preserved, and shared at scale. And now, Gartner has recognized Arch Systems for its role in helping manufacturers meet this challenge.

Arch Systems was recently named a Cool Vendor in the 2025 Gartner Cool Vendors in Manufacturing for Optimizing Performance report, published November 11, 2025.

The report includes providers helping manufacturers improve operational performance. As described in the report’s industry summary:

“This year’s cool vendors leverage AI and advanced analytics to deliver tangible, measurable improvements in operational efficiency, cost reduction, and asset performance across manufacturing. These solutions enable organizations to move from reactive problem-solving to proactive, intelligent optimization.”

For manufacturers facing workforce change and growing operational complexity, this shift from reactive troubleshooting to proactive, intelligence-driven operations is essential.

For decades, manufacturing tribal knowledge helped buffer factories from complexity. But that model is breaking down:

• Experienced technicians are retiring at an accelerating rate
• New workers often don’t stay long enough to build deep expertise
• Electronics and precision manufacturing require specialized skills
• Production schedules can’t tolerate hours of manual troubleshooting
• Data is abundant, but insights are difficult to extract and standardize

This leaves plants exposed. When a problem hits at 2 AM, success still often depends on whether the “right person” happens to be on-site, and whether they’ve seen this exact issue before.

That is no longer sustainable.

Arch Data Twin

Automatically collects, contextualizes, and structures diverse industrial data into an AI-ready foundation without requiring system overhauls or costly rip-and-replace projects.

Arch GLO

Standardizes visibility across lines, processes, and sites to give teams a consistent operational view and a shared set of KPIs across shifts and locations.

Arch AI

Acts as an expert copilot, analyzing data in real time, detecting patterns, and delivering prescriptive recommendations directly to operators, engineers, and leaders.

By combining data, operator input, and real-time context, the Arch platform helps teams understand what’s happening on the factory floor and which actions matter most—turning historically undocumented knowledge into actionable insight.

Manufacturers use the Arch platform to:

• Detect issues earlier and prevent unplanned downtime
• Standardize best practices and decision rules across sites
• Support newer workers with contextual, real-time guidance
• Accelerate decision-making at every level of the factory
• Capture operator input and turn it into institutional knowledge
• Improve asset utilization and overall equipment effectiveness
• Avoid unnecessary capital expenditures by getting more from existing equipment

Arch helps convert manufacturing tribal knowledge into institutional advantage: lessons learned and proven responses are captured, codified, and reused; rather than walking out the door with each retirement or role change.

Across global operations, Arch delivers the actionable intelligence manufacturers need to drive continuous, repeatable improvement at scale.