Why has Mitchell International's Mitchell Estimating solution experienced a 20% increase in support tickets related to parts pricing accuracy in the last 30 days?

Introduction

Mitchell International's Mitchell Estimating solution has experienced a 20% increase in support tickets related to parts pricing accuracy in the last 30 days. This sudden spike in customer issues requires a thorough investigation to identify the root cause and implement effective solutions. I'll approach this problem systematically, examining both internal and external factors that could contribute to the increase in support tickets.

Step 1

Clarifying Questions (3 minutes)

• Considering the timing, I'm wondering if there have been any recent updates to the parts pricing database. Have there been any significant changes to the pricing data sources or update frequency in the last 60 days?

Why it matters: Recent changes could directly impact pricing accuracy. Expected answer: Yes, we switched to a new data provider last month. Impact on approach: If confirmed, we'd focus on data integration and quality issues.

• Given the specificity of the issue, I'm curious about the nature of these tickets. Are the inaccuracies consistently over or under the expected prices, or is there a mix?

Why it matters: Helps identify if the issue is systematic or random. Expected answer: Mostly overpricing, but some underpricing as well. Impact on approach: Consistent overpricing might indicate a calculation error or data issue.

• Thinking about user segments, I'm wondering if this issue is affecting all users equally. Have you noticed any patterns in terms of which customers or regions are reporting these issues more frequently?

Why it matters: Could reveal localized problems or specific user group challenges. Expected answer: The issue seems more prevalent among body shops in the Midwest. Impact on approach: Would focus on regional data sources or user-specific configurations.

• Considering potential system changes, has there been any recent software update or infrastructure change that coincides with the start of this issue?

Why it matters: System changes often introduce unexpected behaviors. Expected answer: We deployed a minor update to the estimating engine two weeks ago. Impact on approach: Would investigate the impact of the recent update on pricing calculations.