What Looks Good Is Not Always What Works

There is a strange pattern in manufacturing today. Many plants have the tools. The systems are connected. The dashboards are green. But the problems are still there. Output misses the target. Teams chase anomalies that do not exist. And smart people spend their time fixing things no one asked them to solve.

This issue of FRAME is about the difference between what looks good and what actually works. You will read how a line operator caught what automation missed. You will see how your most trusted metric might be hiding the truth. And if you are an engineer looking to grow, you will learn how to shift from solving tasks to driving outcomes. These are not tactics. They are patterns of thinking that change how performance is built.

Clarity Outsmarts Complexity

In modern manufacturing, complexity is often mistaken for progress. When teams launch five digital pilots, roll out multiple platforms, and add layers of visualization, it can feel like things are moving forward. The problem is that complexity alone rarely leads to results. The real power lies in clarity & knowing what matters, why it matters, and how to act on it. Without clarity, all the dashboards in the world will only give you prettier confusion.

The Trap of Doing More

Many manufacturing leaders fall into the same well-intentioned trap. They keep adding tools, teams, and tactics because they believe more activity means more improvement. I’ve seen plants layer MES on top of SCADA, add AI-powered maintenance alerts, and then struggle to understand why nothing actually improves.

This happens because complexity creates the illusion of action, while often obscuring the root problem. Uncoordinated projects lead to duplicated efforts. Digital initiatives run in silos. Data becomes harder to trust. Everyone is busy, but few are aligned. The result is an operation that feels modern but functions reactively.

Before starting anything new, ask three questions:

• What specific outcome are we solving for?

• Who owns the result across functions?

• What will we stop doing to make space for this?

If those answers are not crystal clear, you are not solving a problem. You are adding to it.

One Clear Outcome Beats Ten Half Baked Efforts

In a recent engagement, a manufacturer had spent close to a million dollars on analytics tools over the past three years. They had predictive maintenance software, real-time performance dashboards, and an enterprise historian. When I visited their facility, I asked one simple question: which of these tools helped you improve your worst-performing line?

The answer was silence.

They had not identified a weakest link. They had not defined what success looked like for the system as a whole. They had not used any of their tools to solve one core issue from start to finish. It was a perfect case of motion without progress.

To break this cycle:

• Identify a specific operational bottleneck that is costing time or quality

• Align stakeholders from maintenance, operations, and engineering around it

• Use your digital stack only to support that mission, not to prove it exists

Improvement happens when a team builds muscle around solving problems completely. Not when they decorate the process with more tech.

Reflection as a Strategy

The factories that improve year over year are not necessarily the ones with the best automation or newest tools. They are the ones that carve out time to ask what is working, what is not, and why.

One of the most successful leadership teams I’ve worked with has a thirty-minute weekly reflection meeting. No slides. No excuses. Just one question: what did we learn this week that changes how we work next week?

Reflection is not a soft skill. It is a strategic process for sense-making. It enables faster correction, better alignment, and sharper insight. When reflection is built into the culture, people feel less pressure to chase trends and more freedom to stay focused.

If your plant is struggling to make progress despite being “busy,” you do not need more complexity. You need clarity. And that clarity begins when you stop to think.

When an Operator Becomes the Best Sensor

The most expensive software in the world cannot hear a strange vibration or sense hesitation in a machine’s rhythm the way a seasoned operator can. While many plants invest heavily in sensors, PLCs, and machine learning tools to diagnose equipment health and optimize performance, there are still critical insights that come from the people closest to the equipment. Not everything worth knowing is visible on a screen.

This section explores a real-world example from a factory floor where it was not a dashboard or alert that solved the issue, but the human ear. More importantly, it shows how good leadership can make these moments more common and more intentional.

The Case of the Phantom Valve

A mid-sized facility was struggling with inconsistent batch cycle times on one of its core production lines. Some batches would finish on schedule, while others ran five to eight minutes longer, with no clear pattern. The team had deployed every available tool to get to the bottom of it. They combed through the historian, pulled SCADA logs, reviewed alarms, and even introduced a temporary thermal camera to monitor equipment temperature.

Nothing stood out.

It was during a floor walk that one of the line operators, who had worked the same machine for nearly a decade, mentioned that the startup “sounded off” on slower batches. He could not explain exactly what he meant at first, but he insisted something felt different. That comment triggered a closer manual inspection of the system. Eventually, they discovered that a diaphragm valve upstream had started to drift slightly from its set position due to a worn actuator spring. It was opening slower than usual, causing a delayed pressure equalization which affected mixing time.

None of the sensors were sensitive enough to detect the slow change. The actuator’s feedback still reported that the valve was in position. But the process was being impacted. The fix cost under a thousand dollars. The downtime it had been causing was estimated at over seventy thousand dollars per month.

This was not a failure of technology. It was a failure of reliance on technology alone. The lesson is simple: the most powerful diagnostic tool is often a human who knows the process deeply.

People and Data Are Partners

Too often, there is an implicit assumption that data is clean, complete, and sufficient. But all data has gaps. Sensors have blind spots. Systems drift slowly over time. A flow meter can be calibrated. A PLC can be reprogrammed. But an operator who notices subtle changes in how a machine sounds, shakes, or smells is an irreplaceable asset.

That is why advanced systems should not aim to replace operators but to partner with them. Human sensing is not a fallback. It is a parallel system that fills in the blanks where digital tools fall short.

To make this partnership work:

• Capture observations during operator rounds, especially when performance varies

• Add structured “gut check” notes to digital logs where appropriate

• Cross-reference production anomalies with shift logs or verbal reports

Human input is data. It just needs a place to live.

Coaching for Embedded Insights

One of the best things you can do as a technical leader is help your team learn how to listen. Not just to alarms or metrics, but to what the floor is telling you in real time. When I work with site managers or operations leaders, I always include coaching on floor walk strategy.

Here are a few simple but effective practices I have taught:

• Start with open-ended questions like “What feels different today?”

• Walk the floor during changeovers or startups when problems are most likely to emerge

• Use silence. Let people fill it. That is when the real information comes out

• Pair engineers with veteran operators and rotate them across shifts for pattern recognition

The result is not just early detection. It is cultural. Operators start to feel their input matters. Engineers build deeper process understanding. And problems start to get solved before they ever become metrics.

If your factory feels like it is getting smarter but your problems are not going away, it may be time to stop asking for more data and start listening to the people already living inside the process.

Availability Doesn’t Mean Attainment

Availability is one of the most widely reported metrics on the plant floor. It is also one of the most misunderstood. Teams often celebrate high uptime numbers, assuming they are a sign of strong performance. But if the actual output does not match the plan, something is off. The truth is that availability, when used without context, can be deeply misleading. Just because the line is technically running does not mean it is delivering what the business needs.

This section explores the hidden flaws inside availability metrics and offers practical advice on what to track instead. It is a reminder that real performance comes from flow, not from checkmarks.

Why Uptime Numbers Can Lie

I was once working with a food manufacturing plant that reported an availability of over 93 percent on their packaging lines. That would suggest world class performance. But when we looked deeper, they were missing their weekly production targets by 8 to 12 percent consistently. The operators were frustrated. The planners were behind. The managers were confused. On paper, everything looked fine. In practice, it was not.

The problem was how downtime was defined and measured. Micro stops under ten seconds were not recorded. Manual resets were logged as part of run time. Changeovers were treated as planned time regardless of duration. As a result, the availability number looked healthy but it was disconnected from the real experience of operating the line.

This is a common pattern. In many plants, the availability metric gives a false sense of control because it filters out the friction that operators live with every day. If you want the number to mean something, you have to clean up the definition and track what actually interrupts flow.

Measure Human Interruptions

The most valuable signal you can track might not be a classic KPI. It might be something like how often a line requires human input to keep running. In stable operations, human involvement should be intentional and focused. When operators are constantly hitting reset buttons, adjusting speeds, or using joysticks to correct product positions, it tells you that your system is not truly autonomous.

Here are some indicators that often get ignored but reveal more than a percentage ever could:

• Number of operator-initiated resets per shift

• Frequency of stop and start cycles outside scheduled breaks

• Incidents of unattended stops requiring investigation

• Manual overrides of machine logic

This kind of data is hard to get from traditional systems because it lives in gray areas. That is why we recommend working closely with operators and line leads to build logging tools that capture their reality. Even simple paper forms or mobile checklists can surface valuable patterns over time.

If you are interested in exploring better methods for system troubleshooting and root cause visibility, check out Joltek’s post on troubleshooting PLC data structures. It includes practical examples from the field where traditional KPIs failed to expose the real issue.

Go Beyond Rate to Rhythm

A number that looks good over a full shift can still hide volatility. That is why some of the most advanced manufacturers focus on flow-based metrics like average uninterrupted run time or time between interventions. These metrics give you insight into rhythm—the consistency and predictability of the process.

When a line can run cleanly for two or three hours without any touch, you know it is healthy. When it needs to be nudged every few minutes, it is just surviving. In one case, we helped a plant move from a pattern of fifty small stops per shift to just five, by focusing not on increasing rate but on smoothing rhythm. Their availability number barely changed. But their throughput increased by twelve percent.

Think of it this way:

• Rate is how fast you can go

• Rhythm is how long you can stay there without interruption

You need both, but it is rhythm that unlocks performance you can rely on.

Stop Solving Problems That Only You Care About

Many highly capable engineers plateau in their careers not because they lack skill, but because they focus on the wrong problems. They chase technical wins that are invisible to the broader organization. They optimize small systems no one is watching. They spend hours troubleshooting issues that are technically interesting but have little impact on cost, safety, or customer satisfaction. The result is quiet frustration. They feel overlooked. But from the outside, no one sees the value they bring.

This section explores how to shift from being a strong individual contributor to being seen as a strategic player. It is not about working harder. It is about aligning your work with what the business actually cares about.

Do Your Wins Matter to Others?

I once coached a young engineer who had just completed a major optimization of a tank cleaning sequence. He shaved off four minutes from each CIP cycle and was excited to show the logic improvements. When he told leadership, they nodded politely and moved on. He was confused. The work had been smart. But he had missed one thing. The tank was not a bottleneck. The line was waiting on packaging. His work was good, but it did not move the needle.

That is a common pattern.

You cannot earn influence by solving problems that only you understand or care about. If you want to grow in your career, you have to connect your work to something larger. That means:

• Asking how your project impacts other teams

• Aligning with the biggest constraints in the operation

• Tying improvements to financial, safety, or throughput outcomes

When you start selecting your priorities through a business lens, your wins will get noticed. And your name will come up in the right conversations.

Master the Abstract Summary

As you move up, your audience changes. You are no longer explaining your work to other engineers. You are explaining it to plant managers, directors, and VPs who manage dozens of priorities. They do not need to understand the code or the electrical drawings. They need to understand the business case, the risk profile, and the result.

One of the most valuable skills you can build is writing clear, concise, abstract summaries of your work. Think of them as internal memos. Instead of a technical walkthrough, you write a short narrative:

• What problem did we observe?

• What was the risk if left unaddressed?

• What was the chosen solution?

• What did it achieve?

No jargon. No screenshots. No ladder logic. Just impact. If you need help structuring these, you might find value in how we approach project documentation and analysis over at Joltek. It is about clarity that travels.

Once you master this form of communication, you will find that people in the organization start bringing you into broader conversations. They see you as someone who understands not just systems, but strategy.

Grow by Teaching, Not Just Doing

One of the fastest ways to level up your leadership is to teach. When you explain something well to others, you deepen your own understanding. When you help others improve, you multiply your value. And when people around you grow, your influence grows with them.

A few years ago, I started organizing weekly peer sessions for a client’s engineering team. Each week, one person would share a project, a failure, or a technique. These were not formal. No PowerPoint. Just a whiteboard or a live walkthrough of something useful. Within three months, the team’s technical competency improved. But more importantly, their confidence improved. People started reaching across departments. Knowledge became culture. And the engineers who ran those sessions? They got promoted.

Teaching does not require perfection. It requires generosity. It signals maturity. It creates space for others to rise.

Clear Thinking Is a Competitive Advantage

In a world where complexity is easy to buy, clarity is hard to earn. But it is the teams who think clearly, act early, and stay grounded in what matters that actually move the needle. Whether it is catching drift before downtime, choosing better metrics, or communicating work that aligns with the business, progress starts with awareness.

Use this issue as a prompt to reflect. Where are you doing too much? Where are you not listening enough? What are you solving that no one needs? And what could change if you took thirty minutes a week to ask better questions?

That is where performance begins.