3 Must-Track Warehouse Automation KPIs Explained

This article is part of our SME Corner, offering insights from our subject matter experts to guide you on your warehouse automation journey.

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Speed and accuracy aren’t just nice-to-haves in order fulfillment—they’re make-or-break. To keep up, warehouses are turning to advanced automation like Autonomous Mobile Robots (AMRs) and Automated Storage and Retrieval Systems (AS/RS). These tools handle the heavy lifting, moving goods quickly and efficiently throughout the warehouse so teams can focus on higher-value work.

But installing an automated system is just the beginning. Long-term success depends on how well the system’s performance is monitored and maintained. That’s where Key Performance Indicators (KPIs) and system health checks come in.

For AS/RS like the Exotec Skypod system, two important KPIs stand out:

• MMBO (Mean Missions Before Obstruction) – Measures how many missions a robot completes, on average, before it runs into an obstruction—like a blocked path or traffic congestion. 
• MMBI (Mean Missions Before Intervention) – Tracks how many missions are completed before a person needs to step in—for example, to reset the system or fix a robot issue.

These metrics provide valuable insights into how efficiently and reliably the system is operating.

KPIs provide real-time and historical visibility into system performance — and the true value lies in the details. While high-level stats like throughput and system uptime offer a quick overview, it’s the granular KPIs—such as MMBO and MMBI—that uncover deeper operational truths. For supply chain leaders, these metrics are not just technical indicators; they are strategic levers for decision-making. Here’s how:

1. Diagnosing the Why

A system can look healthy on the surface, but a closer look at key KPI trends often uncovers early warning signs. For example, steady throughput might seem like a win—but if the MMBO is quietly declining, it could point to growing congestion, inefficient robot paths, or poor warehouse layout. A lower MMBO might also signal issues like blocked pick stations, crowded racks, or even inconsistent task sequencing.

On the other hand, MMBI tells you how independently the system is operating. A high MMBI means things are running smoothly with minimal human help. But if it starts to fall, it could be a red flag. It may suggest growing reliance on operators due to equipment wear, sensor calibration drift, or even task assignments that robots aren’t equipped to handle. In some cases, it could mean that software updates or operational changes have unintentionally introduced friction into the system.

2. Improved Maintenance Planning

When tracked consistently, MMBO and MMBI become the backbone of predictive maintenance. Instead of servicing equipment based on time intervals, teams can schedule interventions based on actual system usage and performance trends. This minimizes unnecessary downtime, improves robot availability, and ensures technicians focus efforts where they’re most needed.

3. Root Cause Analysis

KPIs are essential in pinpointing why performance dips occur. Let’s say the system’s throughput drops but MMBI remains stable, the issue may lie upstream—such as delayed tote induction or order batching—not with the automated system. Conversely, if MMBI declines, that’s often a direct sign of system-level issues requiring urgent review, such as a specific robot model, zone, or task profile.

4. Performance Benchmarking and Continuous Improvement

Looking at KPI data is like holding up a mirror to your operations—across different sites and shifts. Sometimes the reflection shows what’s working well. Other times, it reveals areas that need fixing. By comparing performance between teams or facilities, you can spot differences in how people work, where training may be lacking, or if your layout is slowing things down. These insights can help you improve continuously by copying what works, updating your standard processes, and making smarter choices about automation.

KPIs show how well the system is performing; system health monitoring explains why it’s performing that way. Together, they form a complete picture. A strong system health strategy means you’re not just reacting—you’re staying ahead of issues before they impact operations. Here’s what that looks like in action for an advanced automation system:

• Battery performance tracking
• Motor and drive diagnostics
• Sensor calibration and alerting
• Traffic analysis and congestion heat mapping
• Real-time alerting for mechanical anomalies

This data helps make sure everything—from robots to conveyors to picking stations—is running smoothly. Even better, it supports predictive analytics that can spot potential issues before they turn into real problems.

For example, if MMBO starts to drop, system health logs can help pinpoint the cause—whether it’s a mechanical issue like worn wheels or an environmental problem like blocked travel paths from misaligned racks. Linking performance data with system health makes it easier to diagnose issues quickly and fix them faster.

The Exotec Skypod system is a high-performance goods-to-person solution designed to handle a wide range of warehouse tasks—including picking, packing, buffering, sorting, and sequencing—all within a single, scalable platform. As part of its built-in intelligence, Exotec continuously tracks key metrics like MMBO and MMBI, giving operators real-time visibility into both the performance and reliability of their systems.

Organizations using Skypod systems and actively monitoring these KPIs alongside system health have achieved measurable gains:

• Reduced downtime through proactive maintenance
• Higher robot availability and throughput
• Improved operator efficiency with fewer manual interventions
• Faster root-cause resolution of operational bottlenecks

During high-pressure periods like the holiday season, this level of visibility becomes a key advantage—keeping fulfillment speeds consistent even when volumes surge.

The success of advanced automation like the Skypod system is rooted in more than just robotics — it’s driven by data. Monitoring KPIs such as MMBO and MMBI, alongside comprehensive system health analytics, is essential for maximizing uptime, optimizing operations, and scaling confidently.

As automation becomes central to modern warehousing, the businesses that invest in robust performance metrics and proactive system health monitoring will not only deliver faster — they’ll operate smarter.

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