Introduction
Root Insurance's sudden increase in customer support wait times for roadside assistance is a critical issue that demands immediate attention. This problem directly impacts customer satisfaction, potentially leading to churn and negative word-of-mouth. I'll approach this analysis systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term and long-term solutions.
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: Understanding the timeline helps identify potential triggers or changes that coincided with the issue. Expected answer: The increase was noticed in the last 2-3 weeks. Impact on approach: A sudden change would point to a specific event or change, while a gradual increase might indicate a systemic issue.
Why it matters: Geographic variations could indicate localized issues or resource allocation problems. Expected answer: The issue is more pronounced in urban areas during peak hours. Impact on approach: This would lead us to focus on urban resource allocation and peak-time management strategies.
Why it matters: Pinpointing the exact stage of delay helps narrow down potential causes and target solutions more effectively. Expected answer: The longest waits occur between the initial customer call and the arrival of assistance. Impact on approach: This would focus our investigation on dispatch systems and service provider availability.
Why it matters: Recent changes could be the source of unexpected issues or bugs affecting service delivery. Expected answer: A new dispatch algorithm was implemented three weeks ago. Impact on approach: This would shift our focus to thoroughly reviewing and potentially rolling back the new algorithm.
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