Why has the average time to complete a cost estimate using aPriori Technologies's Digital Factories increased by 30% since the latest software update?

Introduction

The recent 30% increase in average time to complete a cost estimate using aPriori Technologies's Digital Factories is a significant concern that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

To tackle this issue, I'll follow a structured approach:

1. Clarify the problem and gather essential context
2. Rule out external factors
3. Analyze the product and user journey
4. Break down the metric
5. Prioritize data collection
6. Form and evaluate hypotheses
7. Conduct root cause analysis
8. Propose validation methods and next steps
9. Present a decision framework
10. Outline a comprehensive resolution plan

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this might be related to the latest software update. Can you confirm when exactly the update was released and when the increase in estimation time was first noticed?

Why it matters: Establishing a clear timeline helps identify potential correlations. Expected answer: The update was released X weeks ago, and the increase was noticed Y days later. Impact on approach: A close temporal relationship would strengthen the focus on the update as a primary factor.

• I'm curious about the scope of this issue. Is this 30% increase consistent across all user segments and types of cost estimates, or are there variations?

Why it matters: Understanding the distribution helps narrow down potential causes. Expected answer: The increase varies across segments, with some more affected than others. Impact on approach: Variations would lead to investigating segment-specific factors.

• Considering the nature of Digital Factories, I'm wondering if there have been any changes to the complexity or types of products being estimated recently?

Why it matters: Changes in input could explain output variations. Expected answer: No significant changes in product complexity or types. Impact on approach: If unchanged, this would shift focus to internal system factors.

• Given the significance of this metric, I assume there are monitoring systems in place. Have there been any changes to how this metric is measured or reported?

Why it matters: Ensures we're comparing apples to apples. Expected answer: No changes to measurement or reporting systems. Impact on approach: If changed, we'd need to investigate the measurement process itself.

• Thinking about user behavior, have there been any notable changes in user feedback or support tickets related to the cost estimation process since the update?

Why it matters: User feedback can provide qualitative insights into quantitative changes. Expected answer: Some increase in support tickets related to estimation time. Impact on approach: This would guide us to investigate specific user pain points in the updated system.