How to Analyze Supplier Lead Times in Excel
Start with the sample data
This example uses synthetic business data in USD. Download the CSV and import it through Excel’s Data → From Text/CSV. Set dates to Date, amounts to Decimal Number, and identifiers to Text. The examples use Excel for Microsoft 365 on desktop with English formula names and comma separators.
Download the sample CSV · Data dictionary
Keep an untouched copy of the input. These are educational examples, not customer records or measured customer outcomes.
The result to check
Mean observed lead time: 9.5 days
The mean covers six deliveries with equal weight. Keep planning lead time separate from observed duration.
Build the analysis in Excel
1. Prepare the source and scope
Import operations.csv into a new worksheet with headers in row 1. Leave the source columns in their original order for the formulas below. Review the data dictionary before choosing the reporting period. Keep identifiers as text and convert numeric columns explicitly. Save a working copy so you can return to the original fixture.
2. Build the calculation
Average actual_days across the six example deliveries. Compare each delivery to promised_days and show the range as well as the mean.
=AVERAGE(M2:M7)3. Reconcile and interpret the output
The expected check is mean observed lead time: 9.5 days. The mean covers six deliveries with equal weight. Keep planning lead time separate from observed duration. If your result differs, inspect the selected rows, data types and date filters before changing the formula.
4. Adapt the workflow to a recurring report
Replace the sample with a copy of your own source, retaining the same column meanings and units. Extend bounded ranges to include new rows, refresh PivotTables where used, and compare the result to an independent source total. Record the reporting period and any exclusions beside the output. Calendar days and business days are different measures and must not be mixed.
Checks before using your own data
- Calendar days and business days are different measures and must not be mixed.
- Keep blanks distinct from zero. Investigate missing records rather than hiding errors with a blanket IFERROR formula.
- Verify results after changing filters, sorting rows or appending a new period. The sample output is a check for this fixture, not a forecast for your business.
Tools and reference guides
Continue with your own data
Analyze your spreadsheetSee the supported workflow and upload your file when you are ready. The sample is not loaded automatically.
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