Why has Relex's demand forecasting accuracy for fresh produce declined by 15% over the past month?

Introduction

The recent 15% decline in Relex's demand forecasting accuracy for fresh produce over the past month is a critical issue that requires immediate attention. As we dive into this analysis, we'll systematically explore potential root causes, validate hypotheses, and develop a comprehensive plan to address the problem. Our approach will encompass both short-term fixes and long-term strategic improvements to ensure sustained accuracy in our forecasting models.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal factor at play. Has there been any significant change in weather patterns or growing conditions in our key sourcing regions over the past month?

Why it matters: Seasonal variations can greatly impact fresh produce availability and quality. Expected answer: Unusual weather patterns in certain regions. Impact on approach: If confirmed, we'd need to adjust our forecasting models to account for these seasonal anomalies.

• Considering potential system changes, have there been any recent updates to our forecasting algorithms or data inputs?

Why it matters: Software updates can sometimes introduce unintended consequences. Expected answer: A recent update to incorporate new data sources. Impact on approach: We'd need to review the changes and potentially rollback or fine-tune the algorithm.

• Focusing on data quality, has there been any change in how we're collecting or processing data from our suppliers or stores?

Why it matters: Data integrity is crucial for accurate forecasting. Expected answer: No significant changes in data collection processes. Impact on approach: If there are changes, we'd need to audit our data pipeline and correct any inconsistencies.

• Thinking about market dynamics, have we seen any unusual shifts in consumer behavior or competitor actions in the past month?

Why it matters: External market forces can significantly impact demand patterns. Expected answer: Some shifts in consumer preferences towards certain produce types. Impact on approach: We'd need to adjust our models to account for these new trends and potentially segment our forecasts more granularly.