November 5, 2025 Blind Process Automation Breeds Bigger Problems

Ignorant automation has stark consequences. Understanding today’s tech can help manufacturers adopt more impactful, sustainable solutions.

By Subba Rao, Director of Manufacturing Industries Cloud, Mendix

The manufacturing industry is undergoing a paradigm shift. According to the National Association of Manufacturers, the United States is expected to face a shortfall of 1.9 million manufacturing workers by 2033. As NAM anticipates half of the expected 3.8 million open positions going unfilled, manufacturing stakeholders need to act boldly or increase the likelihood of compounding economic uncertainty, security instabilities, and workforce upskilling risks.

Spurred by this mounting urgency, manufacturers are beginning to recognize that automation is no longer optional but essential to remaining competitive and productive. However, with every possible technology solution now coined as “automation,” picking the right tool can make manufacturers feel like they’re flying blind. Oftentimes, this uninformed implementation leads to automating just for automation’s sake, which can result in consequences such as:

• Financial risks like high upfront costs with low ROI or ongoing hidden costs
• Operational inefficiencies like process misalignment and reduced flexibility
• Workforce challenges like skill mismatches and resistance
• Quality and safety risks like dangerous human-machine interactions and failure oversights
• Strategic risks like technology lock-in and reputational damage

In short, blind automation erodes profitability, flexibility, safety, and employee trust. While adopting these technologies is becoming mission-critical, it is even more critical for manufacturers to establish automation practices that are valuable not only on a program-specific level but also aligned with overall organizational goals to create a competitive edge. Vetting which process automation frameworks are best suited to their unique environments requires that manufacturers know what options are out there, what their best use cases are, and their limitations — for example, long-living transactions in engineering and supply chain versus near-real-time, event-driven processes on the shop floor. Ultimately, the specific use cases and organizational goals dictate returns from each level of automation.

Think Before You Automate

Before implementing any automation tools, manufacturers need to take a step back and fully understand their use case and desired endpoint.

Too often, manufacturers assume that automation alone can solve their challenges and apply process automation as a pilot without identifying root problems, hindering scaling and adaptation down the line. Simply applying automation to a broken process is akin to painting a crumbling house; it may seem better, but the underlying problem remains. Manufacturers dealing with data quality issues, IT-business misalignment, or other process concerns must know these matters won’t disappear with a few bots.

The real question manufacturers need to ask is whether the problem they’re trying to solve is truly an automation issue or a symptom of something deeper. While assessing their current state holistically must come first, the next challenge is knowing which framework to choose.

Not All Automation Is Created Equal

In an age increasingly defined by automation, untying the knot of technology options has never been so important. Several kinds of automation frameworks exist, each with its own strengths and vulnerabilities.

Robotics process automation (RPA)
Robotic Process Automation (RPA) is technology that automates any repetitive business task, such as data scraping, data extraction from PDFs and other documents, data migration, information transfers, form fills, and more.

While these are certainly time-saving opportunities, RPA is difficult to scale and maintain because bots are typically limited in scope. RPA is most effective when each bot has its own dedicated task; however, that means it’s difficult to link bots together to scale your business meaningfully. Any time manufacturing systems update or processes change, RPA systems need to be amended — oftentimes making the upkeep time greater than the time saved through automation.

RPA is a powerful way to automate specific tasks within a larger workflow and works best when integrated with other technologies to achieve true end-to-end automation.  

Commercial off-the-shelf software (COTS)
Commercial off-the-shelf software (COTS) is incredibly easy to work with (hence its name), but there are drawbacks. COTS works best within its specific domain and scope of capabilities — when your needs align perfectly with what the software can offer. But in today’s complex manufacturing landscape, how frequently is that the case?

COTS can be customized, but that requires time, money, and resources. And if manufacturers are considering a highly customized system, what’s the point of using COTS in the first place? This technology should certainly be leveraged when its very domain-specific needs best suit the use case, but if your facility needs something more tailored or sophisticated, there are better routes for automation solutions that could drive a true connected enterprise.

Business process management (BPM)
Business process management (BPM) can help manufacturers analyze, refine, optimize, and improve business processes. BPM vendors can be extremely beneficial for manufacturers looking to automate the business at a more holistic level, breaking down work into step-by-step pieces to see where workflows could be faster and more efficient.

BPM is good for understanding how a process works, designing a better version of that process, and automating the parts that can be. It’s also a great tool for digitizing more complex business processes, such as process modeling, workflow engines, and analytics dashboards, to ensure processes align with business goals. Still, there’s a hint of irony here.

BPM reduces complexity through automation, but can add complexity throughout integration. Manufacturers don’t have a ton of flexibility when it comes to BPM; it can be difficult to implement and is limited in deployment options, particularly when maintaining a critical human-machine loop across a highly fragmented landscape spanning engineering, information, and operational technologies. Other limitations include UI, application logic, and mobile-friendly capabilities. Those needing quick, adaptable application solutions may lean toward different technologies, such as low code.

Low code
Rapid application development via AI-infused low-code platforms uses visual, drag-and-drop interfaces to accelerate software creation. This enables manufacturers to quickly automate processes and digitize workflows for anything from supply chain management to legacy system migration — reducing costs, increasing agility, and making human-in-the-loop interactions possible to help evolve processes that bring initiatives closer to organization goals.

Low code is democratizing the software development landscape, allowing everyone from business stakeholders to on-the-ground workers to be part of the development lifecycle. This collaboration gives rise to applications with process automation capabilities beyond BPM that are more effective and closely aligned to business goals. With process automation that integrates application and workflow automation together, modern, AI-driven low code allows solutions to be created and launched at extraordinary speed and remain adaptable, governable, and scalable.

Automation as a tool, not the end goal

Whether a manufacturer decides to implement RPA, COTS, BPM, low code, or any combination of the above, it’s important to do it with precision, strategy, and, ironically, a human touch.

Imagine a drafty home with a smart thermostat. Just because the house automatically adjusts to an ideal temperature doesn’t fix the real problem: drafts are getting into the structure. In the same way, automation without a clear understanding of the underlying processes, data flows, and human roles only masks deeper inefficiencies. Today, effective digital transformation requires that humans remain in the loop to interpret insights, manage exceptions, and ensure compliance, security, and data integrity.

As organizations accelerate automation, thoughtful human oversight must remain central to maintaining the checks and balances needed for safe, sustainable, and effective operations — especially in an era where the complexity of engineering, information, and operational technologies is high and dynamic.

About the Author:
In his role as Director, Manufacturing Industries Cloud, Subba Rao brings more than 28 years of professional experience (including 17 years with Siemens and three years with Visiprise, which is now part of SAP, and Dassault Systemes) to his role at Mendix. With his deep industrial domain expertise in manufacturing and tech acumen, Rao drives tactical and strategic portfolio and go-to-market initiatives as a low-code and technology thought leader and manufacturing industry evangelist. Rao also advises teams on strategic differentiators for low-code related product innovations as part of Siemens Xcelerator.

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