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Product Management Root Cause Analysis Question: Investigating IT support response time increase for SRM Technologies
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Nextsprints

Updated Jan 22, 2025

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What factors contributed to the sudden 50% increase in response times for Srm Technologies's IT support helpdesk last month?

Problem Solving Data Analysis Process Optimization IT Services Customer Support Enterprise Software
Performance Optimization Root Cause Analysis IT Support Helpdesk Management

Introduction

The sudden 50% increase in response times for SRM Technologies' IT support helpdesk last 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.

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 seasonal factor. Has there been a similar spike in helpdesk requests during this month in previous years?

Why it matters: Seasonal patterns could explain the increase and inform our solution approach. Expected answer: No significant seasonal pattern observed in previous years. Impact on approach: If true, we'd focus more on recent changes or anomalies rather than cyclical factors.

  • Considering the magnitude of the change, I'm wondering about recent system updates. Have there been any significant changes to the helpdesk software or infrastructure in the weeks leading up to this issue?

Why it matters: Recent changes often correlate with performance issues. Expected answer: A minor software update was implemented two weeks prior. Impact on approach: If confirmed, we'd prioritize investigating the impact of this update.

  • Given the specific 50% increase, I'm curious about the distribution. Is this increase uniform across all types of support requests, or are certain categories disproportionately affected?

Why it matters: Uneven distribution could point to specific problem areas. Expected answer: The increase is more pronounced in network-related issues. Impact on approach: We'd focus our investigation on network infrastructure and related support processes.

  • Thinking about potential external factors, has there been any significant change in the customer base or product offerings that might have led to an influx of new or different types of support requests?

Why it matters: Changes in user demographics or product complexity could strain existing support systems. Expected answer: No major changes in customer base or product offerings. Impact on approach: We'd shift focus to internal factors and system capabilities.

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