LinkedIn Reddit Instagram Threads Pinterest

How Excel REGEX Turns Messy Shipment Text into Clean Supply Chain Data

Did you know Excel can now use REGEX (Regular Expressions) to clean and structure complex shipment data? What once required multiple helper columns, LEFT, MID, FIND, and SUBSTITUTE formulas can now be done in seconds using REGEXEXTRACT.

The Real-World Problem

Supply chain teams often receive shipment data as a single text column containing transaction type, shipment date, quantities, returns, and supplier details — all mixed together.

Traditionally, cleaning this data meant:

How Excel REGEX Solves This

With Excel’s REGEX functions, you can directly extract:

By applying REGEXEXTRACT formulas, Excel instantly converts raw shipment text into a clean, structured analytics-ready table.

Why This Matters for Supply Chain Analytics

This approach dramatically reduces processing time, minimizes human error, and enables faster decision-making in supply chain operations and audits.

Key Benefit:

What once took hours using traditional Excel methods now takes minutes using REGEX — making it a must-have skill for analysts and operations professionals.

Explore More from Discover Talent

Subscribe on YouTube Excel for Supply Chain Course Visit Discover Talent Discover Talent GitHub

Tags

Excel Regex, Supply Chain Analytics, Excel Automation, Data Cleaning in Excel, Regexextract Excel, Operations Analytics, Shipment Data Processing, Excel for Analysts