Efficiency Starts Where You Are: Getting More Value from Automation You Already Have

Efficiency has always been a core driver for industrial automation. Long before digitalization and Industry 4.0 became buzzwords, automation was about improving safety, reducing variability and producing quality product with less waste. Today’s operating environment has changed and many facilities are now facing tighter margins, more volatile demand, aging assets and a workforce stretched thin, but improved efficiency goals are as important as ever.

Many facilities are responding to today’s economic challenges with renewed interest in automation and digital tools, but efficiency gains don’t always come from chasing the newest technology. They come from making sure the fundamentals are solid and building from there.

The real constraints: time, money and focus

When conversations about efficiency stall, it’s usually for two reasons: lack of time and lack of money. Most operations teams already have full plates, and capital always has competing priorities. Those constraints are real, but they can also be misleading.

Every facility is already paying for inefficiency in some form: excess energy use, off-spec product, rework, scrap, downtime or manual effort spent working around problems. The question isn’t whether money is available, but whether it’s being spent intentionally on improvement or unintentionally on inefficiency. Improving efficiency involves identifying where those losses occur and redirecting your resources toward changes that reduce waste and pay back over time. 

When improving efficiency, most people will first think of energy or raw material reductions but, depending on the process, reducing off-spec production can be even more impactful.

The same concept applies to time. Internal teams are busy keeping plants running, which is exactly why improvement initiatives tend to slip. That doesn’t mean improvement isn’t possible; it means it needs to be prioritized and approached realistically, starting with what will deliver value fastest. Once you can free up a little time, you can use that time to do bigger things. With this mind, start with something small, such as: Could a new sensor reduce routine maintenance rounds requirements?

Most efficiency losses are basic

Despite industry discussion about machine learning and advanced AI tools, many efficiency losses come from very basic issues. Control strategies that once worked well get disabled, bypassed or slowly drift out of alignment as processes change. Instrumentation fails or degrades and never quite gets brought back to its original performance. Manual workarounds become permanent because no one takes the time to revisit the original problem.

The good news is that these issues are usually quite fixable. That’s why efficiency gains start with simple questions: Is the automation running as designed? Are instruments providing reliable data? Are operators being forced into manual control because the system doesn’t handle real-world conditions?

Fixing what already exists is often the fastest way to improve performance. That often means restoring automation that has degraded over time, such as repairing or supplementing instrumentation so control systems can once again see what the process is doing. Modern instrumentation and data connectivity options make this easier than it used to be, even in hard-to-reach areas. Bringing a process back to its intended level of automation can produce gains without adding new complexity.

Remember, low-hanging fruit is still fruit.

However, it’s critical to remember that no efficiency initiative succeeds without stable process control. It doesn’t matter how advanced a tool is or how new the technology might be; if the underlying process is unstable, anything layered on top will struggle to deliver consistent value.

This has very little to do with the age of the control system. A well-maintained system from decades ago can still support meaningful improvements. It is more important that the process behaves predictably and that control strategies reflect how the plant currently operates today.

Visibility comes before optimization

Once a process is stable, the next step is visibility. Many facilities still operate with islands of automation: stand-alone systems that do their jobs locally but don’t share information. Others collect data but don’t make it accessible in a way that supports day-to-day decisions.

KPIs (key performance indicators) may not be a new concept, but they still provide value when they reflect what matters and are visible to the people who can act on them. That’s why basic visibility tools remain powerful. 

Process historians are another example. A historian that quietly collects data in the background but requires a trip to the control room and a thumb drive to access is not doing much to improve efficiency. Data needs to be available when and where questions arise. If performance isn’t being measured consistently, it’s difficult to improve it. Visibility makes it easier to see what the process is doing and where teams should focus their time.

Know when to push the limits

With stable control and good visibility in place, operations can begin to push performance closer to its limits. This is where more advanced techniques come into play, whether that’s tighter control strategies, predictive tools or systems that help anticipate where a process or batch is headed before it gets there.

The value of these tools is usually incremental rather than dramatic, but those increments add up. Small improvements in yield, energy use or cycle time delivered around the clock can translate into meaningful gains over the course of a year.

Equipment health is another area where specialized or advanced tools can pay off. For example, monitoring valve performance, identifying sticking or poorly sized valves, and catching issues early helps maintain control quality and prevents inefficiencies from creeping back in. These kinds of improvements support both reliability and efficiency at the same time.

It’s also important to recognize that efficient operations depend on people being able to focus on running and improving the process, not working around problems and fighting fires. Poor data quality and unreliable equipment push maintenance and operations teams into a reactive mode of work. When systems are well maintained and provide trustworthy information, downtime is reduced and teams can focus on solving real problems instead of responding to avoidable issues.

Start now, not perfectly

There is always another improvement that could be made and always another technology on the horizon. Waiting for the perfect moment or the perfect solution usually means waiting too long. The best time to improve a process was yesterday. The next best time is now.

Efficiency starts by understanding where you are today, making sure the basics are working as they should and taking the next practical step forward. Progress doesn’t require perfection; it requires starting.

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