What is a Vendor Data Sheet: Excel Structure and Cleaning Guide

If you're working with vendor data sheets but need clarity on what they are and how to clean them, you need a comprehensive guide. 76% of procurement teams use vendor data sheets, but struggle with data quality and cleaning.

By the end of this guide, you'll understand what a vendor data sheet is, its structure, purpose, and how to clean vendor data sheets in Excel for optimal data quality.

Quick Summary

Definition - Structured Excel file containing vendor data for analysis and management
Structure - Vendor attributes, performance metrics, transaction data
Purpose - Vendor analysis, reporting, decision-making, data management
Cleaning - Standardize data, validate accuracy, remove inconsistencies

What is a Vendor Data Sheet?

Definition

A vendor data sheet is a structured Excel workbook containing vendor-related data including vendor attributes, performance metrics, transaction history, and analytical information. It's used for vendor analysis, reporting, and data-driven decision-making.

Purpose

Primary uses:

Vendor performance analysis
Procurement reporting
Vendor comparison
Data analysis and insights
Vendor database management
Business intelligence

Difference from Vendor Information Sheet

Vendor Information Sheet:

Static vendor details
Onboarding information
Master data
Reference document

Vendor Data Sheet:

Dynamic vendor data
Performance metrics
Transaction data
Analytical information

Structure of Vendor Data Sheet

Core Vendor Data

1. Vendor Attributes

Basic Information:

Vendor Code
Vendor Name
Vendor Category
Vendor Type
Registration Date
Status

2. Performance Metrics

Key Performance Indicators:

On-time delivery rate
Quality score
Response time
Cost competitiveness
Overall rating

3. Transaction Data

Business Activity:

Total purchase amount
Number of orders
Average order value
Last order date
Payment history

4. Financial Data

Financial Information:

Credit limit
Outstanding balance
Payment terms
Currency
Bank details

Common Issues in Vendor Data Sheets

1. Data Inconsistencies

Problems:

Mixed formats
Inconsistent naming
Different date formats
Inconsistent number formats

Impact:

Analysis errors
Reporting issues
Decision-making problems

2. Missing Metrics

Problems:

Incomplete performance data
Missing transaction history
Incomplete financial data
Gaps in data

Impact:

Incomplete analysis
Inaccurate reporting
Poor decision-making

3. Calculation Errors

Problems:

Incorrect formulas
Wrong aggregations
Miscalculated metrics
Formula errors

Impact:

Wrong insights
Bad decisions
Reporting errors

4. Outdated Data

Problems:

Old performance metrics
Stale transaction data
Outdated financial info
Not refreshed regularly

Impact:

Outdated insights
Wrong decisions
Inaccurate reporting

How to Clean Vendor Data Sheets

Step 1: Review Data Structure

Understand current structure.

Check Columns

Review:

Column names
Data types
Format consistency
Completeness

Identify Issues

Look for:

Missing columns
Inconsistent formats
Data type mismatches
Structural problems

Step 2: Standardize Vendor Codes

Ensure consistent vendor identification.

Standardize Format

Apply consistent format:

="V-"&TEXT(VALUE(SUBSTITUTE(SUBSTITUTE(A2,"V-",""),"V_","")),"000")

Steps:

Check current format
Choose standard format
Apply to all codes
Verify uniqueness

Step 3: Normalize Vendor Names

Standardize company name formats.

Normalize Names

Apply standardization:

=PROPER(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A2,"Corp.","Corporation"),"Inc.","Incorporated"),"LLC.","LLC"),"Ltd.","Limited"))

Ensure consistency:

Legal suffixes standardized
Case standardized
Extra spaces removed

Step 4: Standardize Date Formats

Ensure consistent date formatting.

Format Dates

Standardize to YYYY-MM-DD:

Select date columns
Format Cells > Date
Choose YYYY-MM-DD format
Apply to all dates

Or use formula:

=TEXT(A2,"YYYY-MM-DD")

Step 5: Standardize Number Formats

Normalize numeric data formats.

Format Numbers

Currency:

Format as Currency
Set decimal places (2)
Choose currency symbol

Percentages:

Format as Percentage
Set decimal places
Ensure values are decimals (0.15 = 15%)

Regular Numbers:

Format as Number
Set decimal places
Add thousands separator if needed

Step 6: Validate Performance Metrics

Ensure metrics are accurate.

Check Calculations

Verify formulas:

Review formula logic
Check for errors
Validate calculations
Test with sample data

Validate Ranges

Check values:

Percentages: 0-100%
Ratings: Within scale (1-5, 1-10, etc.)
Scores: Within valid range
Flags invalid values

Step 7: Clean Transaction Data

Ensure transaction data is accurate.

Validate Amounts

Check:

Positive values (unless credits)
Reasonable amounts
Currency consistency
Decimal precision

Validate Dates

Check:

Valid dates
Logical date ranges
No future dates (unless expected)
Consistent format

Step 8: Handle Missing Data

Deal with incomplete information.

Identify Missing

Find blanks:

Use conditional formatting
Filter for blanks
Count missing per column
Prioritize critical fields

Handle Missing

Options:

Fill with 0 (for numeric)
Fill with "N/A" (for text)
Calculate from other data
Flag for follow-up

Step 9: Remove Duplicates

Eliminate duplicate vendor entries.

Find Duplicates

Method:

Select data range
Data > Remove Duplicates
Check Vendor Code column
Remove duplicates

Verify Removal

After removal:

Check count
Verify no important data lost
Confirm uniqueness

Step 10: Validate and Refresh

Final quality check and data refresh.

Quality Validation

Check:

All formats standardized
Calculations correct
No duplicates
Missing data handled
Data accurate

Refresh Data

Update:

Latest transaction data
Current performance metrics
Updated financial info
Recent status changes

Real Example: Cleaning Vendor Data Sheet

Before (Messy Data Sheet):

Issues:

Inconsistent vendor codes
Mixed date formats
Inconsistent number formats
Missing performance metrics
Calculation errors
Outdated data

After (Clean Data Sheet):

Improvements:

✅ Vendor codes standardized
✅ Dates in consistent format
✅ Numbers properly formatted
✅ All metrics complete
✅ Calculations verified
✅ Data refreshed
✅ Ready for analysis

Best Practices for Vendor Data Sheets

Do's

✅ Do refresh regularly - Update monthly or quarterly
✅ Do validate calculations - Check formulas and results
✅ Do standardize formats - Consistent throughout
✅ Do handle missing data - Fill or flag appropriately
✅ Do document structure - Keep data dictionary
✅ Do backup sheets - Preserve original data

Don'ts

❌ Don't mix formats - Consistency required
❌ Don't skip validation - Accuracy matters
❌ Don't ignore missing data - Handle appropriately
❌ Don't use outdated data - Refresh regularly
❌ Don't skip backups - Risk data loss
❌ Don't ignore errors - Fix calculation issues

Mini Automation Using RowTidy

You can clean vendor data sheets automatically using RowTidy.

The Problem:
Cleaning vendor data sheets manually is time-consuming:

Standardizing formats
Validating calculations
Handling missing data
Refreshing information

The Solution:
RowTidy cleans vendor data sheets automatically:

Upload data sheet - Drag and drop Excel file
AI analyzes structure - Detects all columns and issues
Auto-cleans data - Standardizes formats, validates data
Handles missing data - Fills or flags as appropriate
Exports clean sheet - Get cleaned vendor data sheet

RowTidy Features:

Format standardization - Dates, numbers, text, codes
Data validation - Checks accuracy and completeness
Missing data handling - Fills or flags missing information
Duplicate removal - Finds and removes duplicates
Calculation verification - Validates formulas and results

Time saved: 2-4 hours manual → 10 minutes automated

Clean vendor data sheets automatically with RowTidy. Try RowTidy's data sheet cleaning →

FAQ

1. What is a vendor data sheet?

A vendor data sheet is a structured Excel file containing vendor data including attributes, performance metrics, transaction history, and analytical information for vendor analysis and reporting.

2. How is vendor data sheet different from vendor information sheet?

Vendor information sheet contains static master data for onboarding. Vendor data sheet contains dynamic data including performance metrics and transaction history for analysis.

3. What should be included in vendor data sheet?

Vendor attributes, performance metrics (delivery, quality, cost), transaction data (orders, amounts), financial data (credit, payments), and analytical information.

4. How do I clean vendor data sheets?

Standardize formats (codes, names, dates, numbers), validate calculations and data, handle missing information, remove duplicates, refresh data regularly.

5. How often should I update vendor data sheets?

Monthly minimum, weekly for active vendor management. Update when receiving new transaction data, performance metrics, or vendor updates.

6. Should I validate calculations in vendor data sheets?

Yes. Review formulas, check for errors, validate results, test with sample data. Calculation errors lead to wrong insights and decisions.

7. How do I handle missing performance metrics?

Fill with 0 or "N/A" if not available, calculate from transaction data if possible, flag for follow-up, document missing data reasons.

8. Can I automate vendor data sheet cleaning?

Yes. Use RowTidy to automatically clean vendor data sheets: standardize formats, validate data, handle missing information, remove duplicates.

9. What format should vendor codes be in data sheets?

Standardized format (V-XXX recommended). Consistent throughout sheet. No spaces or special characters except delimiter.

10. Should I backup vendor data sheets before cleaning?

Yes, always. Backup original sheet before any cleaning or updates. Can't recover if mistakes made without backup.

Related Guides

Conclusion

A vendor data sheet is a structured Excel file containing vendor data for analysis and reporting. Clean vendor data sheets by standardizing formats (codes, names, dates, numbers), validating calculations and data accuracy, handling missing information, removing duplicates, and refreshing data regularly. Use tools like RowTidy to automate cleaning and maintain clean, accurate vendor data sheets.

Try RowTidy — automatically clean vendor data sheets and maintain data quality for accurate analysis and reporting.