What caused the sudden spike in customer support tickets related to Planday's shift scheduling feature last week?

Introduction

The sudden spike in customer support tickets related to Planday's shift scheduling feature last week is a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent update to the shift scheduling feature. Has there been any software release or feature update in the past week?

Why it matters: Recent changes often correlate with sudden spikes in support tickets. Expected answer: Yes, there was a minor update to improve scheduling efficiency. Impact on approach: If confirmed, we'd focus on the changes made in that update.

• Considering user segments, I'm curious about the distribution of these tickets. Are they coming from a specific user group or spread across all users?

Why it matters: This helps identify if the issue is universal or specific to certain users. Expected answer: The tickets are primarily from managers of large teams. Impact on approach: We'd investigate factors specific to large team management if this is the case.

• Given the nature of shift scheduling, I'm wondering about any seasonal factors. Are we in a period where scheduling demands typically increase?

Why it matters: Seasonal patterns could explain increased usage and subsequent issues. Expected answer: It's the beginning of the summer season for many businesses. Impact on approach: We'd consider how seasonal demands might be straining the system.

• Thinking about system performance, have there been any reported server issues or downtime recently?

Why it matters: Technical problems could lead to scheduling errors and increased support tickets. Expected answer: No significant downtime, but some users reported slow response times. Impact on approach: We'd investigate backend performance and capacity issues.