KPIs on Day One: What to Measure When Automation Goes Live

SOLUTIONS COMMUNITY

October 27, 2026

Business professional using KPI dashboard data analysis performance metrics growth success strategic business insights in a digital workspace for warehouse automation.

What really matters when the lights come on?

No automation project happens overnight; they are months- and even years-long projects. When the day finally comes to turn on the lights and hit “go,” the entire staff is holding its breath, including the C-suite that backed the expensive project. When they exhale, the next thing they look at are KPIs. But is that really the best place to begin?

Actually, no. Instead, you should use those early days to revisit the statement of work (SOW). This is where you established your operating expectations, and these matter immensely in the beginning. Review items like why you designed the system in the first place—what problem is it there to solve? Look at your order mix, throughput, SKU characteristics, operating hours, exception conditions, interface and more. Most importantly, revisit what the acceptance criteria was.

The reason behind this advice is that there is a big difference between design capacity, contractual performance, operating targets and day one actual performance—you should not treat them as the same number. When you do, you are setting yourself up for the wrong KPI targets. The difference: The SOW tells you what you agreed the system must do; the KPIs tell you what the system and operation are doing.

When you are ready to begin addressing KPIs, your first order of business should be focusing on safety. When you add automation, it will automatically change the rhythm of warehouse activity. Traffic patterns will change and material will move differently. Your associates will be interacting with new equipment, encountering HMI screens, robots, conveyors, sortation equipment and the like—all new additions to the floor. Check on the emergency stops—is someone activating them, and if so, why? How about light curtains or safety zones? Check into all these signs if they’re there, because they indicate that safety isn’t where it should be.

Once you have safety wrangled, then you can focus on other factors, beginning with whether the system is actually flowing. Here check for whether or not the receiving is consistently feeding the operation; whether or not the zones are receiving the right amount of work and that none are missing out; check to see if downstream pack stations can keep up; and whether or not the ASRS is waiting for replenishment, and the like. These are more important health checks than throughput numbers, at least to start.

You’ll also want to contextualize your uptime. For instance, a conveyor can be available, but it might also be waiting for product. The same with a robot and/or an ASRS. Operations should understand the difference between equipment being down, being starved, blocked, or simply sitting idle because there is no demand. Each of these conditions require different responses, and day-one visibility should make them visible.

Also measure recovery, not just failure. Watch how effectively an operation identifies, responds to, and recovers from faults—this can be as or more important than the actual number of faults. Also pay attention to exceptions, which may give you more information than normal flow. Exception handling should have its own KPI visibility. Monitor numbers like how many cartons the system rejects; how many orders require manual intervention; how many barcode no-reads are occurring, and the like. Your goal isn’t necessarily zero exceptions on day one, but to understand those exceptions.

Keep quality in mind, also, because it matters when you automate. Day one should involve strong quality measures alongside throughput. Track scan accuracy, sort accuracy, pick accuracy and damages. Data quality matters as well, so make sure the system can reconcile during go-live.

When it comes to your labor KPIs, you’ll also want to exercise patience, as it is too early to declare success or failure. Your operators are still learning the new systems, you may still have integrators on site, your maintenance crew will be nearby, and you may have scheduled your processes to run below full volume. Measure KPIs like touches per order, operator interventions, productivity, and how much time you spend resolving exceptions. But treat those numbers as baseline and a diagnostic tool during the initial ramp up.

Don’t overlook the service level agreement (SLA) either. It should define who and what happens when something requires support. Who owns the issue? What is the expectation for response vs resolution? Together, these form a simple chain: SOW → SLA → KPI → Process. The SOW defines what was agreed. The SLA defines how the system will be supported. The KPIs tell you what is actually happening operationally. The process tells the organization what to do about it. When you get those four elements aligned, the operation has better odds of stabilizing quickly.

As you go live, keep in mind that a single operational source of truth should guide you. Agree on your operational scoreboard before going live. Remember that day one is baseline, not the finish line. Don’t wait until go-live to decide what success looks like. A successful day one is not one where nothing goes wrong. Instead, it’s one where the operation can see what is happening, understand why it’s happening, respond effectively and become better with every shift.

Before beginning your next warehouse automation project, visit the Solutions Community website and download the SOW Guidelines.

Contributor: Onur Uranli, Intelligrated

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