How can we explain the sudden 25% decline in data accuracy for Quantela's Traffic Management platform across multiple city deployments in the past two weeks?

Introduction

The sudden 25% decline in data accuracy for Quantela's Traffic Management platform across multiple city deployments in the past two weeks is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both immediate and long-term implications for our product and users.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, metrics, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan to resolve the issue and prevent future occurrences.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent software update. Has there been any significant changes or updates to the platform in the last month?

Why it matters: Recent changes could directly impact data accuracy. Expected answer: Yes, there was a minor update two weeks ago. Impact on approach: If confirmed, we'd focus on the update's contents and rollout process.

• Considering the multi-city nature, I'm wondering about data sources. Have there been any changes in how we're collecting or processing traffic data from various cities?

Why it matters: Changes in data collection could affect accuracy across deployments. Expected answer: No changes in data collection methods. Impact on approach: If unchanged, we'd look more closely at data processing or integration issues.

• Given the specific 25% figure, I'm curious about our measurement methods. How exactly are we defining and measuring data accuracy for this platform?

Why it matters: Ensures we're addressing the right metric and not a measurement error. Expected answer: Accuracy is measured by comparing sensor data to manual traffic counts. Impact on approach: Confirms the metric is reliable, focusing our efforts on actual data issues.

• Noticing it's across multiple cities, I'm wondering about user behavior. Have we seen any changes in how city officials or traffic managers are using the platform recently?

Why it matters: User behavior changes could indirectly affect data accuracy. Expected answer: No significant changes reported in user behavior. Impact on approach: If confirmed, we'd prioritize technical or data-related hypotheses over user-centric ones.