Manufacturers are operating with very little margin for inefficiency. Labor shortages are limiting capacity, reshoring is driving up demand for domestic production, and expectations around quality and throughput keep rising.
It’s no surprise that many are turning to automation. Robotics, vision systems, material handling, and integrated controls all offer a path to doing more with less manual labor.
But even with how far these technologies have come, a lot of automation projects still fall short. Systems don’t perform as expected, bottlenecks don’t go away, and sometimes new problems show up altogether.
In most cases, the issue is how the project was defined long before any equipment was installed.
How Automation Projects Usually Start
Most automation efforts follow a familiar path. A need is identified, and almost immediately the solution is framed around a specific technology: often robots or vision systems. At the same time, budgets and timelines are established early.
The challenge is that these decisions are often made before anyone has taken a step back to evaluate the broader production system or consider the full range of possible solutions.
By the time automation specialists or engineering teams are brought in, the project is already boxed in. Layouts are fixed, expectations are set, and there is limited opportunity to question the original assumptions.
At that point, automation is treated less as a problem-solving exercise and more as a purchase decision. The focus shifts toward implementing a predefined solution rather than determining whether it is the right one in the first place.
Why This Approach Doesn’t Work
Starting with a predefined solution creates a few predictable challenges.
It narrows the field too early. When teams begin with a specific technology in mind, they tend to move toward it even when simpler changes to material flow, handling, or layout could deliver meaningful improvements with less cost and complexity.
Early decisions are hard to unwind. Once budgets, layouts, and timelines are set, they tend to stick even if new information suggests a different direction would be better. Without room to test or compare alternatives, teams move forward with an incomplete picture.
Automation often gets treated as a fix for a single point instead of a system-wide change. Improving one station can create new inefficiencies somewhere else because everything in a production system is connected.
When automation is scoped too narrowly or too early the consequences usually don’t show up until after installation, when changes are harder and more expensive. The result:
- Systems that are over-specified relative to actual needs
- Equipment that is underutilized because it does not align with the process
- Bottlenecks that move rather than disappear
- Increased maintenance and training requirements
- Higher levels of scrap, rework, or inefficiency
These issues reflect decisions that were made without a full understanding of how the system would operate.
What to Do Instead
A better approach is to treat automation as a series of decisions, not a single one. Start with the process, not the technology. Bring together engineering, maintenance, and operations teams early in the discussion.
Look at a range of options from small, targeted improvements to larger system changes and consider how each affects the overall production flow. Upfront thinking creates flexibility. It gives teams the ability to compare approaches, test assumptions, and align solutions with real operational goals.
It also reduces the likelihood of expensive course corrections later.
Real-World Examples
Here are a couple of examples of what I’ve seen in the field:
A manufacturer facing fast-growing demand initially assumed that facility expansion or robotics would be required to meet production targets. Rather than moving directly to that solution, however, the team decided to step back and evaluate their full production flow. By replacing manual cart and rack movement with a conveyor-based system and applying targeted automation where it added the most value, they were able to significantly increase output without expanding the facility or disrupting operations.
In another case, a manufacturer was dealing with a critical piece of equipment that had become unreliable due to an aging control system. The initial assumption was that the entire machine would need to be replaced, which would be costly and disruptive. Instead, the team stepped back and evaluated what was causing the issue. Rather than replacing the full system, they rebuilt the control panel, upgraded the drives and motors, and modernized the controls.
By focusing on the root problem instead of defaulting to a full replacement, they were able to restore production capacity, extend the life of the existing equipment, and avoid a much larger capital expense.
In both these cases, the outcome wasn’t driven by more advanced technology. It came from taking the time to better understand the problem before choosing a solution.
That’s where a lot of automation efforts go sideways. Decisions get made early, before there’s a full picture of how the process works or what options are on the table. A more effective approach is to slow that part down just enough to evaluate the system as a whole, bring the right perspectives into the conversation, and explore options before committing to a path forward.
It doesn’t necessarily mean doing something more complex. In many cases, it means doing something simpler but doing it more intentionally. And that work happens well before anything gets installed.
Sam Karimi is General Manager of the Motion Systems Group at Motion & Control Enterprises (MCE). He oversees a multi-state organization within Motion Systems, covering fluid power and automation solutions. Learn more at MCEautomation.com.
