73% of Meeting Room Failures Are Preventable. Here's the Data.

The first question we asked when building Emily — Spacera's Automated L1/L2 Tech — was a simple one: what percentage of meeting room failures could theoretically be detected and resolved before a user was impacted?

The answer surprised us.

73%.

Not 30%. Not 50%. Nearly three in four meeting room failures could have been caught and fixed automatically, before the first person walked into that room.

Here's what we found.

What actually causes meeting room failures

There's a widespread assumption in IT that meeting room failures are primarily hardware failures. A camera dies. A codec bricks. A display fails.

These do happen. But they're not the majority.

When we categorized failures across the fleet data Emily processes, the breakdown looked like this:

Configuration drift — 31%

Rooms quietly fall out of their expected configuration state over time. A Teams update changes a default. A firmware push introduces an incompatibility. A room gets moved and its network settings aren't updated. The room looks fine until someone tries to use it.

Credential and authentication failures — 22%

Service accounts expire. Certificates lapse. API tokens rotate and aren't updated. The room authenticated fine yesterday; today it can't reach the platform backend.

Network and connectivity issues — 20%

Not full outages — partial. A port that's being throttled. A proxy that's blocking a signalling protocol. A VLAN that lost its QoS marking after a switch firmware update. The room connects, but call quality degrades or camera discovery fails silently.

True hardware failures — 15%

The camera actually dies. The codec won't boot. The display loses its HDMI handshake. These happen — but they're the minority, not the majority.

Other (peripheral, software, user error) — 12%

Why 73% are preventable

Failures in the top three categories — configuration drift, credential failures, network issues — share a critical property: they generate signals before the user is impacted.

A service account that's about to expire has been expiring for days. A certificate has an expiry date. Configuration drift is measurable against a known baseline. Network degradation shows up in latency and packet loss statistics hours before it causes a user-visible failure.

Emily runs automated morning testing at 6 AM — before the workday starts. She validates every peripheral, authenticates every platform connection, checks every network path, and compares the room state against its known-good baseline.

When she finds an anomaly, she doesn't raise a ticket and wait. She acts. Remote reboot. Config reset. Credential refresh. 73% of the time, the issue is resolved before anyone walks in.

The other 27%? Hardware failures and complex issues that genuinely need a human. Those get escalated — with full context — to your ITSM tool and your support team.

What this means for your team

If 73% of your meeting room failures are resolved automatically before they impact a user, your engineers stop being reactive firefighters and start being proactive architects.

The 3 AM call that was a credential expiry? Emily handles it.

The Monday morning scramble because a room didn't come back from the weekend correctly? Emily handles it.

The CEO's board room that worked fine on Friday and failed on Monday? Emily caught the drift on Sunday night.

Your engineers own the 27%. They get context-rich tickets, not "the camera isn't working" calls.

That's what Automated L1/L2 Tech means. Not a chatbot. Not a self-service portal. Actual automated resolution — at the speed of code, at the scale of your fleet.

Read the Emily Technical Overview →