Manufacturing has always demanded precision, control, and quality. Today, it also demands agility, resilience, efficiency, and the ability to pivot without grinding production to a halt.
That is where open, software-defined automation is making a difference. Think less hardware lock-in, more adaptability. Less firefighting, more flow. In a word: Schmoooth. And the numbers show why this shift is picking up speed.
A 2026 global survey of consumer packaged goods (CPG) and life sciences manufacturers found that inefficiencies such as downtime, delays, and equipment failure already account for 20-20.3% of total production cost, with manufacturing revenue lost to preventable issues like rework, quality deviations, and suboptimal asset use. Those losses are projected to climb sharply, approaching nearly 30% by 2030 if left unaddressed.
The Cost of Standing Still
Most industrial automation was built for a different era. Long before cloud, AI, and high-performance edge computing showed up to the plant. No surprise, it struggles to keep up.
Today’s manufacturing environment moves faster and requires more agility. Energy prices swing. Demand shifts. Efficiency targets get tighter. Regulations pile on. But many systems are still locked into rigid, hardware-bound control models that were never designed for this kind of pace.
So, when something changes, things get... clunky.
Instead of adjusting in software, teams face physical upgrades, workarounds, and delays. Agility slows. Risk creeps in. Costs climb.
And the numbers make it hard to ignore.
Mid-sized manufacturers lose an average of $10+ million each year to inflexible, closed systems; about 7.5 % of revenue slipping away through downtime, complexity, and missed opportunities. For large manufacturers, that number jumps to nearly $50 million. Smaller players feel it even more, sometimes losing up to a quarter of revenue when they cannot adapt.
Waiting does not help. Delays can cost millions in lost value.
Definitely not schmoooth.
What Open, Software-Defined Automation Changes
If you have heard the term but wondered what open, software-defined automation means or why it matters right now, let’s break it down in plain language.
Open, software-defined automation separates control logic from dedicated hardware. Instead of intelligence being locked inside proprietary controllers, it lives in software that can run across open, standard-based platforms.
The practical effect is simple.
Changes happen in software instead of through rewiring, reprogramming, or hardware replacement. That alone solves massive problems manufacturers are dealing with right now.
This shift is also foundational for industrial AI. Many manufacturers recognize AI’s potential, yet only 13% say it is fully embedded across operations today. By 2030, that number is expected to reach 37%, highlighting how quickly organizations are working to connect automation, data, and AI into a unified system.
Open, software-defined automation replaces those rigid change cycles with faster, repeatable updates. Hardware is no longer the anchor. Control logic is built once and deployed anywhere.
Physical assets (drives, sensors, motors) remain unchanged; only the control layer is virtualized. By decoupling software from hardware, organizations gain flexibility without disrupting physical assets or proven operations.
Small Batches Should Not Mean Big Losses
Today’s manufacturing reality is defined by product variety and shorter life cycles. The systems behind production have not always kept up.
The research shows manufacturers lose about 8% of order volume, over $1 million annually, simply because legacy systems cannot efficiently support smaller or more customized orders.
For smaller manufacturers, losses tied to minimum batch constraints can climb above 20%.
At the same time, manufacturing production complexity is climbing fast. In high-mix manufacturing environments, plants commonly shift from producing a handful of products to dozens or even hundreds of distinct product types, with significantly higher variant counts layered on top.
Open, software-defined automation helps absorb that complexity without multiplying engineering effort or downtime.
Downtime Is Still the Silent Momentum Killer
Downtime is not just a maintenance problem. It is an architecture problem.
Manufacturers now juggle between two and more than ten automation platforms at a single site, each with its own tools, dependencies, and specialists.
That fragmentation shows up in hard numbers:
- 30% of maintenance activities require vendor-specific support
- Nearly one quarter of facilities experience 10 to 24 hours of full production stoppage every month
- For large manufacturers, unplanned downtime costs around $75,000 per hour
- Open, software-defined automation reduces that drag by simplifying architectures and removing vendor lock-in.
Data Is Everywhere. Insight Is Not.
Industrial AI, advanced analytics, and digital twins all rely on one thing: Quality data that flows freely.
But nearly half of manufacturers report that 40 to 59% of their critical operational data is not available in real time due to system limitations.
Only 28% can get real time insights today. The rest wait hours or days.
That gap costs money.
- Over $1 million annually spent managing fragmented data
- Between $1 million and $5 million lost each year to preventable quality issues tied to delayed insight
- Open, software-defined automation creates a cleaner data foundation, making industrial AI practical instead of theoretical.
AI Expectations are Rising Faster Than Results
Manufacturers are betting heavily on AI to unlock efficiency but results today are still uneven. About 70% report current AI ROI below 20%, with nearly a third seeing 5% or less.
At the same time, expectations are accelerating. By 2030:
- 32.7% of manufacturers expect AI ROI between 50 and 74%
- 7.9% expect returns above 100%, meaning investments pay back in under a year
Closing this gap depends less on new AI tools and more on the systems that support them. Open, software-defined automation plays a critical role integrating information technology (IT) and operational technology (OT) for the data consistency, connectivity, and quality that AI depends on.
What Early Movers Are Seeing
Manufacturers that have adopted open, software-defined automation are already seeing measurable improvements.
- 30% lower design and engineering costs
- 40 % fewer errors during development
- Up to 50 % faster engineering and commissioning
- 20% less engineering time and far easier replication across sites
Keep It Schmoooth
Manufacturing is not getting simpler, and inefficiencies are becoming more costly every year. As production losses rise and AI expectations climb, the ability to integrate data, automation, and intelligence into a single, adaptable system is becoming a core competitive advantage for industrial operators.
Open, software-defined automation makes that possible. It turns change into a competitive advantage, aligns data with decision-making, and creates the foundation that industrial AI needs to deliver real results at scale.
Manufacturing, but Schmooother.
Learn how automation runs schmooother with Schneider Electric.
And visit Schneider Electric at Automate 2026, in South Building Booth #2257
This blog is sponsored by Schneider Electric
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