Got a problem to resolve!

It should start with What’s the Problem, Really?

Let’s start with the basics: what’s the problem we’re trying to solve?

In many engineering environments, especially fast-paced ones, we often find ourselves firefighting, patching issues, reacting to failures, and optimizing things that maybe shouldn’t exist in the first place. The real problem is that we’re solving symptoms, not root causes.

Take, for example, a recurring bottleneck in a production line. Every few weeks, throughput drops, and everyone scrambles to fix it. We add sensors, tweak software, retrain staff, but the issue keeps coming back. Why? Because we haven’t asked the deeper question: should this process even exist in its current form?

So the problem isn’t just inefficiency. It’s misalignment between what we’re doing and what we should be doing. And that’s worth solving.

Should We Solve It?

Now, before we jump into solutions, let’s ask: is this worth solving?

Here’s a simple framework to decide:

• Impact: Does solving this problem significantly improve performance, reduce cost, or enhance quality?
• Frequency: Is this a one-off issue or a recurring pain point?
• Visibility: Does this problem affect customers, stakeholders, or compliance?
• Scalability: Will solving it here help us elsewhere too?

If the answer to most of these is “yes,” then we’re not just solving a problem, we’re unlocking value.

In our bottleneck example, solving it could mean:

• 20% more throughput
• Less overtime
• Happier operators
• Better data for future improvements

So yes, we should solve it. But not with duct tape. We need a real solution.

How Do We Solve It?

Here’s where things get interesting.

Solving a problem like this isn’t just about fixing what’s broken. It’s about reimagining the process. That means stepping back and asking:

• What is the process trying to achieve?
• What constraints are we working within?
• What would this look like if we designed it from scratch?

Let’s say the bottleneck is in packaging. Maybe the root cause isn’t the machine, it’s the way orders are batched. Or maybe it’s the layout of the workspace. Or maybe it’s the software logic that prioritizes jobs.

To solve it, we need to:

1. Map the current process (warts and all)
2. Identify failure modes and inefficiencies
3. Engage the people who live with the process daily
4. Prototype alternatives
5. Test and iterate

This isn’t a one-time fix. It’s a mindset shift, from reactive to proactive, from patching to engineering.

Process Engineering – Designing the Solution

Now let’s get into the nuts and bolts.

Process engineering is about designing workflows that are efficient, reliable, and scalable. Here’s how we approach it:

Step 1: Process Mapping

Use tools like SIPOC (Suppliers, Inputs, Process, Outputs, Customers) or value stream mapping to visualize the entire flow. Don’t just map what’s supposed to happen, map what actually happens.

Step 2: Data Collection

Gather cycle times, failure rates, downtime logs, operator feedback. This is your evidence base.

Step 3: Root Cause Analysis

Use methods like 5 Whys or Fishbone diagrams to dig into why things go wrong. Often, the real issue is upstream. It is typically not a operator but operations from jr. field operator all the way up yo sr. plant management.

Step 4: Redesign

Now, sketch out a new process. Maybe it’s a layout change, a software tweak, or a new scheduling algorithm. Keep it lean. Keep it modular.

Step 5: Simulation & Testing

Before rolling out changes, simulate them. Use digital twins or simple spreadsheets. Then pilot the new process in a controlled environment.

What Does the Solution Look Like?

The final solution should be:

• Robust: Handles variability without breaking
• Simple: Easy to understand and maintain
• Scalable: Works across teams or sites
• Data-driven: Monitored with KPIs and feedback loops

In our packaging example, maybe the solution is:

• A new batching algorithm that balances workload
• A redesigned workstation layout that reduces movement
• A dashboard that alerts operators before bottlenecks form

But more importantly, the solution is a culture of continuous improvement. One where problems are surfaced early, solved collaboratively, and prevented from recurring.