Root Cause Analysis
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This category investigates the underlying causes of performance issues, helping teams make data-driven decisions by identifying what drives trends and anomalies.
Hint: Drill-down analysis typically follows anomaly detection. Once an anomaly or outlier is identified, drill-down techniques help determine its root cause.
Purpose: Lumi AI allows users to dig deeper into specific causes behind patterns using historical chats. Users first identify performance issues or inefficiencies and analyze the contributing data points.
Typical Prompts:
Isolate Issues: "Identify the top 5 suppliers with the highest number of late deliveries over the past 6 months. Include relevant details like average delay time and regions affected." Follow-up : "What is the number of late deliveries for XYZ supplier over the last 12 months?."
Isolate Issues: "Identify the products with the highest rate of out of stocks in Q2 2023. Include details such as warehouse locations and supplier names."
Follow-up: "Show me the historical out of stocks rates for these ABC product over the past 12 months, broken down by warehouse."
Isolate Issue: What items have experienced the largest decline in gross profit when comparing the past 3 months to the previous 3 months.
Follow Up: For item LR-E0059, what is the gross profit for every month in the last 12 months along with the moving average?
Isolate Issue: Can you show me total sales revenues for every day in May?
Follow Up: Investigate the reasons behind the negative revenues on May 10 and May 24.