Back to Articles
Best Practices

How Should You Clean Up the Vendor List: Best Practices Guide

Learn the best practices for cleaning up vendor lists in Excel. Discover the recommended approach, order of operations, and methods to ensure thorough and efficient vendor data cleaning.

RowTidy Team
Nov 27, 2025
14 min read
Vendor List, Data Cleaning, Excel, Best Practices, Vendor Management

How Should You Clean Up the Vendor List: Best Practices Guide

If you're unsure about the best approach to clean your vendor list, you need a proven methodology. 79% of companies clean vendor data incorrectly, leading to duplicate payments, ERP import failures, and procurement delays.

By the end of this guide, you'll know exactly how you should clean up your vendor list—following best practices, proper order of operations, and efficient methods that ensure data quality.

Quick Summary

  • Follow systematic order - Clean in specific sequence for best results
  • Start with duplicates - Remove duplicates before standardizing
  • Standardize then validate - Format first, then check accuracy
  • Document everything - Keep records of changes made
  • Test before finalizing - Verify cleaned data before ERP import

The Recommended Cleaning Order

Why Order Matters

Wrong approach:

  • Standardize formats first
  • Then remove duplicates
  • Result: Wasted time standardizing duplicates that get deleted

Right approach:

  • Remove duplicates first
  • Then standardize formats
  • Result: Efficient, no wasted effort

Recommended Sequence

  1. Backup original data
  2. Remove duplicates
  3. Standardize vendor codes
  4. Normalize company names
  5. Validate contact information
  6. Standardize addresses
  7. Handle missing data
  8. Mark active/inactive status
  9. Validate data quality
  10. Export clean vendor master

Step 1: Backup Original Data

Always start with a backup.

Why Backup First

Risks without backup:

  • Accidental data loss
  • Can't recover original
  • No comparison reference
  • Can't undo mistakes

How to Backup

Method 1: Save As

  1. Open vendor list
  2. File > Save As
  3. Name: "vendor_list_backup_2025-11-27.xlsx"
  4. Save in separate folder
  5. Original preserved

Method 2: Copy Sheet

  1. Right-click sheet tab
  2. Move or Copy
  3. Check Create a copy
  4. Name: "Original Backup"
  5. Keep original intact

Best practice: Keep backup for 90 days minimum.

Step 2: Remove Duplicates (First Priority)

Remove duplicates before any other cleaning.

Why Duplicates First

Benefits:

  • Reduces dataset size
  • Prevents duplicate standardization work
  • Eliminates confusion
  • Speeds up remaining steps

Duplicate Detection Methods

Method 1: Excel Remove Duplicates

  1. Select data range (including headers)
  2. Data > Remove Duplicates
  3. Check columns:
    • Vendor Code (primary)
    • Vendor Name (secondary)
    • Tax ID (tertiary)
  4. Click OK
  5. Excel shows count removed

Method 2: Formula Detection

=COUNTIF($B$2:$B$1000, B2)>1

Returns TRUE for duplicate vendor codes.

Method 3: Conditional Formatting

  1. Select vendor code column
  2. Home > Conditional Formatting > Highlight Cells Rules > Duplicate Values
  3. Duplicates highlighted
  4. Review before deleting

Which Duplicates to Remove

Remove these:

  • Exact duplicates (all columns same)
  • Duplicate vendor codes
  • Duplicate tax IDs
  • Fuzzy name matches (review first)

Keep these:

  • Different locations of same vendor (different codes)
  • Historical records (if needed)
  • Verified unique entries

Step 3: Standardize Vendor Codes

Establish consistent vendor code format.

Why Standardize Codes

Problems with inconsistent codes:

  • ERP import failures
  • Lookup errors
  • Reporting issues
  • System integration problems

Standardization Rules

Choose format:

  • V-001, V-002, V-003 (recommended)
  • VENDOR-001, VENDOR-002
  • V001, V002, V003
  • Custom format (company standard)

Apply consistently:

  • All codes follow same pattern
  • Same length
  • Same prefix/suffix
  • No spaces or special characters (except delimiter)

Excel Method

Standardize to V-XXX format:

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

Steps:

  1. Insert helper column
  2. Enter formula
  3. Copy down
  4. Paste as values over original
  5. Delete helper column

Step 4: Normalize Company Names

Standardize vendor company names.

Normalization Rules

Legal entity suffixes:

  • Corp → Corporation
  • Inc. → Incorporated
  • LLC → LLC (keep as is)
  • Ltd. → Limited

Case standardization:

  • Use Title Case (recommended)
  • Or Proper Case
  • Consistent throughout

Remove extra characters:

  • Extra spaces
  • Special characters (unless part of name)
  • Punctuation inconsistencies

Excel Method

Normalize legal suffixes:

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

Apply Title Case:

=PROPER(TRIM(A2))

Combine:

  1. Apply suffix normalization
  2. Apply case standardization
  3. Remove extra spaces
  4. Verify results

Step 5: Validate Contact Information

Ensure contact data is accurate and complete.

Validation Rules

Email addresses:

  • Must contain @ symbol
  • Must have valid domain
  • No spaces
  • Standard format

Phone numbers:

  • Standardize format: (XXX) XXX-XXXX
  • Remove extra characters
  • Validate country codes if international

Contact names:

  • Proper case
  • No special characters (unless part of name)
  • Complete (first and last if applicable)

Excel Validation

Validate email:

=IF(AND(ISNUMBER(SEARCH("@",A2)), ISNUMBER(SEARCH(".",A2, SEARCH("@",A2)))), "Valid", "Invalid")

Format phone:

="("&LEFT(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A2,"(",""),")",""),"-",""),3)&") "&MID(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A2,"(",""),")",""),"-",""),4,3)&"-"&RIGHT(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A2,"(",""),")",""),"-",""),4)

Flag missing:

  1. Use conditional formatting
  2. Highlight blank cells
  3. Fill or flag for follow-up

Step 6: Standardize Addresses

Normalize address formats for consistency.

Address Components

Standardize:

  • Street suffixes (St. → Street, Ave. → Avenue)
  • City names (proper case)
  • State abbreviations (consistent format)
  • ZIP codes (5-digit or ZIP+4 format)
  • Country codes (if international)

Excel Method

Standardize street suffixes:

=SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A2,"St.","Street"),"Ave.","Avenue"),"Rd.","Road"),"Blvd.","Boulevard"),"Dr.","Drive")

Format ZIP codes:

=TEXT(A2,"00000")

For 5-digit ZIP codes.

Step 7: Handle Missing Data

Deal with incomplete vendor information.

Missing Data Strategy

Required fields:

  • Vendor Code (must have)
  • Vendor Name (must have)
  • Tax ID (required for most systems)
  • Contact Email (preferred)

Optional fields:

  • Phone number
  • Secondary contact
  • Payment terms
  • Notes

Handling Methods

Fill missing:

  • Use "Unknown" or "N/A" for optional fields
  • Contact vendor for required fields
  • Flag for follow-up

Remove incomplete:

  • Only if too many missing required fields
  • Document why removed
  • Keep in separate sheet for follow-up

Step 8: Mark Active/Inactive Status

Separate active vendors from inactive ones.

Status Categories

Active:

  • Currently doing business
  • Recent transactions
  • Valid contracts

Inactive:

  • No recent activity
  • Closed/Terminated
  • Merged/Acquired

Excel Method

Add status column:

=IF(OR(B2="Closed", B2="Inactive", B2="Terminated"), "Inactive", "Active")

Filter by status:

  1. Add filter to Status column
  2. Filter to "Active" only
  3. Copy to new sheet
  4. Active vendor list ready

Step 9: Validate Data Quality

Final quality check before export.

Quality Checks

Completeness:

  • All required fields present
  • No critical missing data
  • Coverage acceptable

Accuracy:

  • Vendor codes unique
  • Tax IDs valid format
  • Contact info correct
  • Addresses complete

Consistency:

  • Formats standardized
  • Naming conventions followed
  • Data types correct

Validation Report

Create checklist:

  • No duplicate vendor codes
  • All vendor codes standardized
  • Company names normalized
  • Contact info validated
  • Addresses standardized
  • Missing data handled
  • Status marked
  • Ready for export

Step 10: Export Clean Vendor Master

Export in format required by your system.

Export Formats

Excel (.xlsx):

  • For manual review
  • For sharing
  • For documentation

CSV:

  • For ERP import
  • For system integration
  • Universal format

Custom format:

  • ERP-specific templates
  • SAP vendor master
  • Oracle vendor format

Required Columns

Minimum:

  1. Vendor Code
  2. Vendor Name
  3. Tax ID
  4. Address
  5. Contact Email
  6. Status

Optional:

  • Phone
  • Payment Terms
  • Currency
  • Bank Details
  • Notes

Best Practices Summary

Do's

✅ Do backup first - Always save original
✅ Do remove duplicates first - Before standardization
✅ Do standardize systematically - One format at a time
✅ Do validate thoroughly - Check before export
✅ Do document changes - Keep records
✅ Do test import - Verify in target system

Don'ts

❌ Don't skip backup - Risk data loss
❌ Don't standardize duplicates - Waste of time
❌ Don't mix cleaning steps - Follow order
❌ Don't skip validation - Quality matters
❌ Don't export untested - Verify first
❌ Don't delete original - Keep backup

Real Example: Proper Cleaning Order

Scenario: 5,000 vendor records

Step 1: Backup

  • Saved original as "vendor_backup_2025-11-27.xlsx"

Step 2: Remove duplicates

  • Found 250 duplicates
  • Removed, kept best record
  • 4,750 vendors remaining

Step 3: Standardize codes

  • Converted all to V-XXX format
  • All codes consistent

Step 4: Normalize names

  • Standardized legal suffixes
  • Applied Title Case
  • Names consistent

Step 5: Validate contacts

  • Fixed 150 invalid emails
  • Standardized 200 phone numbers
  • 95% contact completeness

Step 6: Standardize addresses

  • Normalized street suffixes
  • Formatted ZIP codes
  • Addresses consistent

Step 7: Handle missing

  • Filled 50 optional fields
  • Flagged 25 for follow-up
  • 99% required fields complete

Step 8: Mark status

  • 4,200 active
  • 550 inactive
  • Status clear

Step 9: Validate quality

  • All checks passed
  • Ready for export

Step 10: Export

  • Exported as CSV
  • Imported to ERP successfully
  • No errors

Time: 3 hours (manual) vs 10 minutes (automated)

Mini Automation Using RowTidy

You can clean vendor lists following best practices automatically using RowTidy.

The Problem:
Following best practices manually is time-consuming:

  • Proper order of operations
  • Systematic standardization
  • Thorough validation
  • Quality assurance

The Solution:
RowTidy follows best practices automatically:

  1. Upload vendor list - Drag and drop
  2. AI analyzes data - Detects all issues
  3. Applies best practices - Follows proper order
  4. Validates quality - Ensures accuracy
  5. Exports clean master - Ready for ERP

RowTidy Best Practices:

  • Backup creation - Saves original automatically
  • Duplicate removal first - Before standardization
  • Systematic cleaning - Proper order of operations
  • Quality validation - Comprehensive checks
  • Export ready - ERP-compatible formats

Time saved: 3-6 hours manual → 10 minutes automated

Follow best practices automatically with RowTidy. Try RowTidy's vendor cleaning →

FAQ

1. What order should I clean vendor data?

Remove duplicates first, then standardize codes, normalize names, validate contacts, standardize addresses, handle missing data, mark status, validate quality, then export. Order matters for efficiency.

2. Should I backup before cleaning?

Yes, always. Backup original data before any cleaning. Can't recover if you make mistakes without backup.

3. Why remove duplicates before standardizing?

Removing duplicates first reduces dataset size, prevents wasted standardization work on duplicates, and speeds up remaining steps. More efficient approach.

4. How do I know if cleaning is complete?

Create validation checklist: no duplicates, codes standardized, names normalized, contacts validated, addresses standardized, missing handled, status marked, ready for export.

5. Should I test cleaned data before ERP import?

Yes, always. Test import in staging environment first, verify data quality, check for errors, then import to production. Prevents system issues.

6. How often should I clean vendor lists?

Quarterly minimum, monthly recommended for 100+ vendors. Clean when receiving vendor updates, after mergers/acquisitions, or when noticing data quality issues.

7. Can I automate vendor list cleaning?

Yes. Use RowTidy for automated cleaning following best practices. Saves time and ensures consistency.

8. What if I make mistakes during cleaning?

If you have backup, restore original and start over. If using RowTidy, original is preserved automatically. Always backup first.

9. Should I clean all vendors or just active ones?

Clean all vendors, but separate active from inactive. Keep inactive for historical reference, but mark clearly. Clean both for complete master.

10. How do I maintain clean vendor data?

Establish data entry standards, validate at entry, regular cleaning schedule, use automated tools like RowTidy, train staff on standards, monitor data quality.

Related Guides

Conclusion

You should clean up vendor lists following a systematic order: backup first, remove duplicates, standardize codes, normalize names, validate contacts, standardize addresses, handle missing data, mark status, validate quality, then export. Following best practices ensures efficient, thorough cleaning. Use tools like RowTidy to automate the process and ensure consistency.

Try RowTidy — automatically clean vendor lists following best practices and proper order of operations.