Introduction
The unexpected 30% spike in support tickets for Blue Yonder's Warehouse Management System (WMS) over the past 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 fixes and long-term strategic implications.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into product understanding, metric breakdown, and hypothesis generation. We'll then conduct a thorough root cause analysis, propose validation methods, and outline a comprehensive resolution plan.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with support spikes. Expected answer: Yes, a major update was rolled out. Impact on approach: If yes, we'd focus on the update's features and potential bugs.
Why it matters: Helps identify if it's a universal issue or segment-specific. Expected answer: The increase is primarily in enterprise customers. Impact on approach: If segment-specific, we'd tailor our investigation to that user group.
Why it matters: Rules out normal seasonal variations. Expected answer: This increase is atypical for the season. Impact on approach: If seasonal, we'd compare to historical data for context.
Why it matters: Ensures the increase isn't due to measurement changes. Expected answer: No changes to the support ticket system. Impact on approach: If changed, we'd need to recalibrate our analysis based on the new system.
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