Almost every manufacturer can point to an automation pilot that worked. A predictive-maintenance model that caught a failing bearing. A vision system that flagged defects a human missed. A dashboard that finally made the line legible. The hard part was never the pilot. It's everything after.

The pattern is so common it has a name. McKinsey calls it “pilot purgatory,” and its research has repeatedly found that at least 70% of manufacturers are stuck there, with significant activity underway but no meaningful bottom-line impact, and fewer than a third ever scaling a solution company-wide. The technology usually works. The program is what fails.

This report is about why, and the failures are not random. They repeat, plant to plant, from the same root causes: data that was never ready, systems that couldn't talk to each other, models nobody trusted, and people who were never brought along. Each lesson pairs what we see in the field with the public evidence that shows how widespread it is, and what to do differently.

The seven lessons

The pilot proves nothing about the rollout. A pilot succeeds in controlled conditions with everyone watching. Scale removes every one of those advantages at once, and the gap between “it worked once” and “it works everywhere” is where most automation budgets quietly disappear.
Bad data sinks good models. Automation built on siloed, inconsistent, or missing data inherits every one of those flaws. There's no algorithm that fixes a data foundation nobody laid.
Integration is where the value dies. The factory floor and the business systems were built in different worlds and still speak different languages. Only about 30% of manufacturers can get real-time data to the people who need it.
A model nobody trusts is a model nobody uses. A predictive system that generates alerts the team doesn't believe, and therefore doesn't act on, isn't a maintenance system. It's an expensive dashboard.
Connecting the floor without securing it. Every new connection is a new way in, and manufacturing has been the most ransomware-targeted sector in the world for four years running. Security can't be a later phase.
Chasing the shiny use case instead of the valuable one. The boring, bankable win, the small share of assets causing most of the downtime, often goes unaddressed while the exciting demo gets the budget.
Buying a product when you needed a capability. The plants that succeed treat automation as a capability they build, not a license they purchase. A tool your team can't operate is a liability with a fee attached.

Backed by the evidence, not just opinion

Every figure in the report traces to a named third-party source, McKinsey, Deloitte, and IDC among them, and each lesson pairs that public evidence with Plaxonic's own view from building and running these systems. The report also includes a figures section visualizing the failure patterns, and a six-question readiness checklist you can run against any automation initiative before the technology arrives.

Who it's for

Plant and operations leaders, manufacturing IT and OT teams, and executives deciding where to invest in automation, and how to rescue a program that has stalled.

Written by the Plaxonic engineering team, drawing on real-world experience delivering automation and AI in manufacturing. Every figure in the report is traced to a named third-party source; sections marked “Plaxonic's View” are our own perspective.

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