Diagnosing the Hidden Constraint Behind a COVID Crisis

When Everything Was Moving — but Nothing Was Working

This was a moment made for a Diagnostician.

The system wasn’t broken — but it was failing, fast. When COVID hit, our telehealth platform went from handling hundreds of visits a day to tens of thousands almost overnight. Patients couldn’t get through. Calls dropped. Physicians timed out. Support queues overflowed. The default assumption was clear: we’d hit a capacity wall.

Every team leapt into action. Engineering scrambled to scale infrastructure. Ops triaged support. Product patched the user experience. But despite everyone’s effort, nothing moved fast enough — because we weren’t solving the same problem. The system was in motion — but misfiring. Alignment had quietly unraveled. That’s when I stepped in.

The Diagnostician’s Role

I pulled cross-functional leads into a war room and paused the reactive scramble. Before throwing more effort at the fire, I asked a single question: “What exactly is driving this overload?” Not what it looked like — what was actually underneath it? That question changed everything.

The Diagnosis

We discovered that a massive share of demand wasn’t from patients seeking care — it was from people trying to access COVID testing. At the time, testing access was limited and confusing. Many were routed into virtual visits not because they needed a doctor, but because the system didn’t offer another way in. It wasn’t a bandwidth failure. It was a triage failure — the hidden constraint behind the chaos.

The Response

Found the Root Constraint
We traced the overload not to clinical volume, but to routing failure — the system didn’t distinguish care needs from information needs.

Redirected Non-Clinical Traffic
We launched a self-service testing flow to absorb and reroute testing-related demand outside the care queue.

Rebalanced System Load
We adjusted pricing to prioritize clinical time, and introduced time-based nudges to flatten usage spikes and stabilize throughput.

The Results

  • 40% reduction in unnecessary virtual visits
  • System stability restored within days
  • Clinician burnout reduced, patient experience improved
  • Teams moved from parallel reactions to focused, coordinated progress

That’s the role I play when systems stall. I diagnose the root constraint, realign the moving parts, and reconnect the system — so it can breathe again.