Once you have visibility into your machines, your labor, and your jobs, the question becomes: Now what?
With so much data flowing in, it’s easy to feel overwhelmed and to try to fix everything at once. But that rarely works. Spreading your efforts too thin leads to stalled projects, team fatigue, and little long-term impact.
That’s why Step 4 is all about focus and using your data to identify your most impactful opportunities.
Improvement efforts fail when teams chase surface-level issues or the wrong priorities. You might get pressure to “do something,” but if it’s not the right thing, it wastes time and energy.
Instead of reacting, this step helps you:
This is where visibility becomes strategic.
Let’s say you’ve been tracking labor and machine performance, and you notice a recurring pattern:
A specific high-mix job has long setup times, inconsistent cycle times, and frequent inspection delays.
That job might only run a few times a week—but it’s throwing off your schedule every time. Instead of launching a blanket “reduce downtime” initiative, you zero in on that job and what’s causing friction.
Or maybe you identify that a single machine—let’s say your most versatile turning center—is running below 50% utilization during second shift. With real data in hand, you can dig into why. Is it a staffing issue? A training gap? Poor handoff from first shift?
This kind of focused insight allows you to:
And because it’s data-backed, you can track results and prove what’s working.
To identify your top opportunities:
The goal isn’t to fix everything overnight—it’s to fix the right thing first.
The best CI project isn’t the biggest one—it’s the one that makes a measurable difference.
And with the right visibility, that difference is easier to find—and act on—than you think.