Let me know if this sounds familiar.
You’re sitting there, looking at your flow metrics.
Your cycle time spikes, and your throughput drops compared to last week.
Your heart sinks, and your first instinct is to think, “Something’s off. Do we need to fix this? Is the team slowing down? Did we drop the ball somewhere?”
That gut reaction? I completely get it. I’ve been there.
But here’s the thing. And this is where the real problem lies:
When you’re focusing too much on comparing your results side by side without stepping back to think about the natural variation that’s always happening in your process, you’re setting yourself (and your team!) up for failure.
Here’s what typically happens.
You see that spike in cycle time, and suddenly, you’re in firefighting mode. You start digging, looking for what’s “broken,” and scrambling to figure out how to fix it. Maybe you even gather the team, telling them the numbers don’t look good this week and something has to change. And the urgency kicks in. Sound familiar?
Here’s what I want you to understand: not every deviation in your metrics means something is wrong.
Let me say that again—most of the time, those shifts are just part of the normal variation in your workflow.
Here’s where things get tricky.
When you treat every little dip in throughput or spike in cycle time as a red flag, you’re constantly second-guessing yourself, your team, and the process. You end up reacting to the wrong signals and making unnecessary adjustments.
This is where it gets dangerous.
You might start tweaking the process—maybe adding new policies, changing your WIP limits, or even restructuring your team—all because of something that might not even be a problem.
You’re all working harder, but are you really making things better? Not necessarily.
Here’s what you need to know: not every fluctuation in your data is a crisis.
Don’t try to fix issues that aren’t really issues. You’re probably making things worse by doing that. You’re spinning your wheels, trying to solve problems that don’t exist, and in the process, you’re creating new ones.
I want to help you break free from that.
Here’s the truth you need to internalize: variation is normal.
It’s just a part of how systems work. Cycle times will fluctuate. Throughput will go up and down. WIP might spike one week and stabilize the next. These changes are not always signs of a problem.
If your team’s cycle time is a little longer than usual this week, does that automatically mean something is broken? No, it could just be that you had a couple of larger tasks in the queue, or maybe the team was focused on more complex work.
But here’s the real question: where do you draw the line between normal variation and a real issue that needs attention?
How do you know when to take action?
You can’t (and shouldn’t!) react to every single change. What you need is a system in place that helps you make the right decisions at the right time. And that’s where setting thresholds comes in.
Setting a threshold means defining what’s considered “stable” for your process. It’s about understanding the typical range of variation and using that to determine when something genuinely needs your attention because it’s putting your performance into question.
In the next article, “Natural Process Limits 101: How to Set Thresholds That Drive Continuous Improvement”, we’ll dive deeper into exactly how to set those thresholds and figure out what “stable” really looks like for your process. I’ll show you how to use the tools you already have to make reliable data-driven decisions that guide your improvement initiatives.
But for now, here’s what I want you to do: take a deep breath and remember this—not every bump in the data is a reason to sound the alarm. Sometimes, it’s just part of the ride. And that’s okay. Let things flow, trust the process, and know when to act.
Thanks for tuning in, and I’ll see you next Thursday, same time and place, for more managerial goodness! Until then, take care.
