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Product Management Root Cause Analysis Question: Investigating increased support response times for AssetWorks EAM solution
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Nextsprints

Updated Jan 22, 2025

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What factors are contributing to the increased customer support response times for AssetWorks's EAM solution in the past month?

Problem Solving Data Analysis Customer Experience Enterprise Asset Management IT Services Facilities Management
Product Metrics Root Cause Analysis Enterprise Software Customer Support AssetWorks

Introduction

AssetWorks's Enterprise Asset Management (EAM) solution is experiencing increased customer support response times over the past month. This issue directly impacts user satisfaction and the overall effectiveness of the product. I'll approach this problem systematically, focusing on identifying potential root causes, 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)

  • Looking at the timing, I'm thinking there might be a recent change in the product or support system. Has there been any significant update or change in the EAM solution in the last 1-2 months?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on the update's impact; if no, we'd look at gradual changes or external factors.

  • Considering the nature of EAM solutions, I'm wondering about the complexity of recent support tickets. Have you noticed any change in the types of issues customers are reporting?

Why it matters: Changes in issue complexity can significantly affect response times. Expected answer: There's been an increase in complex, technical issues. Impact on approach: If true, we'd focus on technical training and documentation; if not, we'd look at other factors affecting response time.

  • Given the importance of user segments, I'm curious about the distribution of increased response times. Are all customer segments equally affected, or are certain types of users experiencing longer wait times?

Why it matters: Segmentation helps identify if the issue is universal or specific to certain user groups. Expected answer: Enterprise clients are more affected than small business users. Impact on approach: If segmented, we'd tailor solutions to specific user groups; if universal, we'd look at system-wide factors.

  • Thinking about potential system changes, I'm wondering about the support infrastructure. Have there been any recent changes to the customer support tools or processes?

Why it matters: Support system changes can directly impact response times. Expected answer: A new ticketing system was implemented recently. Impact on approach: If yes, we'd focus on system adaptation and training; if no, we'd look at other operational factors.

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