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Product Management Root Cause Analysis Question: Investigating sudden increase in Skydio's obstacle avoidance support tickets
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Nextsprints

Updated Jan 22, 2025

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Asked at Skydio

15 mins

How can we explain the sudden 25% increase in customer support tickets related to Skydio's obstacle avoidance system in the last two weeks?

Data Analysis Problem Solving Technical Understanding Consumer Electronics Robotics Aerospace
Product Improvement Data Analysis Root Cause Analysis Customer Support Drone Technology

Introduction

The sudden 25% increase in customer support tickets related to Skydio's obstacle avoidance system over the past two weeks 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 implications for our product strategy.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into our product ecosystem, user journey, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan to resolve the issue and prevent future occurrences.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might have been a recent software update. Has there been any change to the obstacle avoidance system's firmware or software in the last month?

Why it matters: Software changes often lead to unexpected behaviors. Expected answer: Yes, a minor update was pushed two weeks ago. Impact on approach: If confirmed, we'd focus on regression testing and code review.

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

Why it matters: Helps identify if it's a universal issue or specific to certain users. Expected answer: Tickets are primarily from newer users. Impact on approach: If true, we'd investigate onboarding processes and user education.

  • Regarding performance metrics, has there been any change in the actual performance of the obstacle avoidance system, or just an increase in reported issues?

Why it matters: Distinguishes between perception issues and actual performance degradation. Expected answer: No measurable change in system performance. Impact on approach: If confirmed, we'd focus on user communication and expectations.

  • Thinking about environmental factors, have there been any significant changes in typical flying conditions for our users in the past two weeks?

Why it matters: External factors could be challenging the system's capabilities. Expected answer: No notable changes in flying conditions. Impact on approach: If unexpected changes are reported, we'd need to adapt our system for new scenarios.

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