What's causing the sudden increase in error rates for the Celonis Task Mining feature across multiple client deployments?

Introduction

The sudden increase in error rates for Celonis Task Mining across multiple client deployments is a critical issue that demands immediate attention. This problem not only affects our clients' ability to leverage our product effectively but also poses a risk to our reputation and customer satisfaction. In addressing this challenge, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this might be related to a recent update. Has there been any significant software release or configuration change in the past few weeks?

Why it matters: Recent changes often correlate with sudden performance shifts. Expected answer: Yes, a minor update was pushed last week. Impact on approach: If confirmed, we'd focus on changes in that update.

• Considering the multi-client nature, I'm wondering about infrastructure. Have we seen any unusual patterns in our cloud resource utilization or network performance?

Why it matters: Infrastructure issues could explain widespread problems. Expected answer: No significant changes in cloud metrics. Impact on approach: If true, we'd shift focus to application-level issues.

• Given the specificity to Task Mining, I'm curious about data inputs. Have there been any changes in the types or volumes of data being processed recently?

Why it matters: Changes in input data can sometimes trigger unexpected behaviors. Expected answer: Some clients have increased their data volume. Impact on approach: We'd investigate data processing pipelines and scalability.

• Thinking about user behavior, have we noticed any changes in how clients are interacting with the Task Mining feature?

Why it matters: Unusual usage patterns could be triggering errors. Expected answer: No significant changes observed in user behavior. Impact on approach: We'd focus more on system-level issues rather than user-related causes.