What factors are contributing to the increased error rates in Aspen Technology's Aspen Schedule Optimizer for refinery planning over the last month?

Introduction

The increased error rates in Aspen Technology's Aspen Schedule Optimizer for refinery planning over the last month present a critical issue that demands immediate attention. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Our analysis will follow a structured framework, beginning with clarifying questions to establish context, ruling out external factors, understanding the product and user journey, breaking down the metric, gathering and prioritizing data, forming hypotheses, conducting root cause analysis, and finally proposing validation methods and next steps.

Step 1

Clarifying Questions (3 minutes)

• Given the timing, I'm thinking there might have been a recent update or change. Has there been any software update or configuration change to the Aspen Schedule Optimizer in the past 1-2 months?

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 the nature of refinery planning, I'm curious about the specific types of errors we're seeing. Are these optimization errors, data input errors, or output inconsistencies?

Why it matters: Different error types point to different root causes. Expected answer: Primarily optimization errors. Impact on approach: This would guide our technical investigation and data analysis focus.

• Looking at user segments, I'm wondering if this is affecting all refineries equally or if there's a pattern. Are certain types of refineries or specific geographic regions experiencing higher error rates?

Why it matters: Segmentation can reveal underlying patterns or isolated issues. Expected answer: Higher impact on complex refineries in North America. Impact on approach: We'd investigate factors specific to affected segments.

• Considering potential external factors, have there been any significant changes in refinery operations or market conditions that might be stressing the system in new ways?

Why it matters: External changes can push systems beyond their designed parameters. Expected answer: Oil price volatility has increased. Impact on approach: We'd examine how market volatility impacts the optimizer's performance.

• Thinking about system dependencies, has there been any change in the data sources or integrations that feed into the Aspen Schedule Optimizer?

Why it matters: Input quality and consistency are crucial for optimization accuracy. Expected answer: No known changes to data sources. Impact on approach: If changed, we'd investigate data quality; if not, we'd focus on internal processing.