Why has the average processing time for Saama's Trial Planning & Forecasting module increased by 20% in the last two weeks?

Introduction

The recent 20% increase in average processing time for Saama's Trial Planning & Forecasting module is a critical issue that demands immediate attention. This performance degradation could significantly impact user satisfaction, operational efficiency, and ultimately, the product's market position. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent update. Has there been any software deployment or configuration change in the last two weeks?

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

• Considering user behavior, have we seen any changes in usage patterns or data volume processed by the module recently?

Why it matters: Increased load or changed usage could explain performance drops. Expected answer: No significant changes noted. Impact on approach: If yes, we'd investigate scaling issues; if no, we'd focus more on internal system factors.

• Given the specificity of the increase, I'm curious about our monitoring setup. Has there been any change in how we measure or define processing time?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd need to recalibrate our analysis; if not, we can trust the reported increase.

• Thinking about system dependencies, have there been any changes or issues with integrated systems or data sources?

Why it matters: External dependencies can significantly impact processing times. Expected answer: Some API latency issues reported with a third-party data provider. Impact on approach: If yes, we'd investigate the integration points; if no, we'd focus more on internal optimizations.