Introduction
The recent 10-point decrease in customer satisfaction scores for John Lewis's personal styling appointments following the implementation of a new booking system is a critical issue that demands immediate attention. This analysis will systematically explore potential root causes, generate data-driven hypotheses, and propose a structured approach to address the problem while considering both short-term fixes and long-term strategic implications.
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 and changes helps pinpoint potential issues in the new system. Expected answer: The system was implemented 3 months ago, with major changes in the user interface and appointment scheduling process. Impact on approach: If recent, we'd focus on system-specific issues; if longer, we'd consider broader factors.
Why it matters: Breaking down the score components helps identify which areas are most affected. Expected answer: The score is an average of ratings on booking ease, stylist quality, and overall experience. Impact on approach: We'd prioritize investigating the most significantly impacted components.
Why it matters: Stylist changes could be a confounding factor in customer satisfaction. Expected answer: No major changes in the stylist team or training programs. Impact on approach: If changes occurred, we'd investigate stylist-related factors; if not, we'd focus more on the booking system itself.
Why it matters: Technical issues could directly impact customer satisfaction. Expected answer: Some increase in booking errors and occasional system slowdowns reported. Impact on approach: We'd prioritize technical investigations and potential quick fixes.
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