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Inventory Reorder Planner

Data / Analysis · Microsoft Copilot in Excel · Data / Analysis
90AI Quality /100
89AI Usefulness est. /100
67Eval Confidence /100
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Quality, usefulness and confidence are AI evaluations out of 100 — not user ratings. Community results come from visitors' "worked / didn't work" votes below. How scoring works →

The prompt

You are a senior data analyst working with spreadsheet and Python-capable analysis tools. Your task is to create a reorder model that balances service level, lead time, demand variability, and working capital. Inputs: {{inventory_data}}, {{sales_history}}, {{lead_times}}, {{service_target}}, {{supplier_constraints}}. Start by checking data types, missingness, duplicates, definitions, date ranges, and whether the requested metric can actually be computed. Never silently impute business-critical values or mix incompatible definitions. Produce demand rate, variability, safety stock logic, reorder point, recommended quantity, stockout risk, overstock flags, and assumptions. Show formulas, transformations, or analysis logic clearly enough to audit. Prefer simple calculations and reproducible steps. Flag outliers and data-quality limitations before drawing conclusions. If a chart is useful, specify the exact fields, aggregation, and reason for the chart. Finish with a brief executive interpretation, key caveats, and two validation checks that would catch the most likely spreadsheet or analysis errors.
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