What factors are contributing to the sudden 30% increase in wait times for Teladoc's mental health consultations this month?

Introduction

The sudden 30% increase in wait times for Teladoc's mental health consultations this month is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our telehealth service.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product ecosystem. We'll break down the metric, gather relevant data, form hypotheses, and conduct a thorough root cause analysis. Finally, we'll develop a comprehensive plan to validate our findings and implement solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has there been a similar increase in wait times during this month in previous years?

Why it matters: Seasonal patterns could indicate predictable demand fluctuations. Expected answer: No significant seasonal pattern observed in previous years. Impact on approach: If seasonal, we'd focus on capacity planning; if not, we'd investigate recent changes.

• Given the specific 30% figure, I'm curious about our measurement accuracy. Have there been any recent changes to how we calculate or report wait times?

Why it matters: Ensures we're addressing a real issue, not a measurement anomaly. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd audit the new system; if not, we'd focus on actual wait time factors.

• Considering user segments, I'm wondering if this increase is uniform across all mental health specialties or concentrated in specific areas?

Why it matters: Helps pinpoint if the issue is systemic or specialty-specific. Expected answer: Increase is more pronounced in certain specialties. Impact on approach: If uniform, we'd look at overall system capacity; if varied, we'd investigate specialty-specific factors.

• Thinking about recent product changes, have we implemented any new features or processes in the past month that might affect consultation scheduling or delivery?

Why it matters: Recent changes often correlate with performance shifts. Expected answer: A new scheduling algorithm was implemented two weeks ago. Impact on approach: If changes occurred, we'd scrutinize their impact; if not, we'd look at external factors or gradual trends.