VBA Merge Multiple Excel Files: The Slow Way (And the FAST Fix)

If you’re trying to build a reliable script for VBA merge multiple excel files, you’ve likely discovered that this 30-year-old method is frustratingly slow, brittle, and prone to breaking. If you’ve ever stared at a folder containing dozens of Excel files, one for every sales rep or region, and dreaded the manual copy-paste routine required to combine them, you know exactly how painful that workflow is.

Many of us try to solve this by Googling for a VBA macro, only to find that the script is incredibly slhttps://fromexceltopython.com/blog/vba-macro-slow/ow, prone to crashing, or silently corrupts the data. This post breaks down the technical bottlenecks that make VBA a “robot arm” ill-suited for bulk data processing and introduces a modern “factory” method using Python and Pandas. We look at a simple, five-line script that can stack 50 files in seconds, keeping your data clean and your sanity intact.

You’re here because you have a painful, repetitive task. It’s the end of the week, or the end of the month, and you have a folder sitting on your desktop. It’s filled with 10, 20, or maybe 100 different Excel files—one from each store, each sales rep, each region.

Your job? Combine them all into one, single “Master” spreadsheet.

The first time you did it, you used the “manual” way. You opened the first file, copied the data, pasted it. Opened the second file, copied, scrolled down, pasted. By the tenth file, you were bored. By the 50th, you were going insane, and you knew you’d made a copy-paste error somewhere.

So, you got smart. You Googled “how to automate merging Excel files.” And every single search result pointed you to VBA.

You’re trying to build a VBA merge multiple excel files script. Maybe you found a 50-line code snippet online, or you’re trying to record a macro. And you’ve hit a wall. It’s incredibly slow, it crashes Excel, and it’s so fragile you’re terrified it’s silently corrupting your data.

You’re right to be frustrated. You’re using a 30-year-old tool for a modern data problem. This article will explore why your VBA merge multiple excel files script is so slow and unreliable, and then show you the modern, robust, and lightning-fast alternative.

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Why Your VBA Merge Script is a Nightmare (The Technical Reasons)

VBA (Visual Basic for Applications) is slow for one fundamental reason: it’s a “robot arm” designed to interact with the Excel application. It literally mimics a human clicking, selecting, copying, and pasting. It’s not a true data processing tool.

This “robot arm” design creates three massive bottlenecks that make your merge script a failure.

Bottleneck #1: The Open / Close Overhead (The “Physical” Delay)

The core of your VBA merge script is a loop. And inside that loop, it has to perform physical file operations over and over again.

Your code probably looks something like this:

Set MyFolder = fs.GetFolder(“C:\My_Reports”)

For Each MyFile In MyFolder.Files

‘ This is Bottleneck #1: Opening the file

Set wb = Application.Workbooks.Open(MyFile.Path)

' ... (copy-paste logic) ...

‘ This is Bottleneck #1 again: Closing the file

wb.Close

Next MyFile

This looks logical, but it’s catastrophically slow. Why? Because Workbooks.Open is not a simple command. You are forcing Excel to:

1. Read the entire file from your hard drive (slow).
2. Load the entire Excel application (the ribbon, the UI, the fonts).
3. Calculate any formulas in that file (slow).
4. Render the spreadsheet on your screen (even if you can’t see it).

You are forcing Excel to fully open and close 50 different applications. This is not a data operation; it’s a 50-step administrative nightmare. This alone is why your VBA merge multiple excel files process feels like it takes forever.

Bottleneck #2: The Select / Copy / Paste Nightmare (Cell-by-Cell)

The next part of your loop is where the “robot arm” really shows its weakness.

‘ … (inside the loop) …

‘ Find the last row of data to copy

lRow = wb.Sheets(1).Cells(Rows.Count, 1).End(xlUp).Row

‘ Select the data

Range(“A2:Z” & lRow).Select

‘ Copy to clipboard

Selection.Copy

‘ Switch to the Master workbook

ThisWorkbook.Activate

‘ Find the *next* empty row to paste

lPasteRow = ThisWorkbook.Sheets(1).Cells(Rows.Count, 1).End(xlUp).Row + 1

‘ Select the paste location

Range(“A” & lPasteRow).Select

‘ Paste from clipboard

ActiveSheet.Paste

This is horrifyingly inefficient. You are forcing Excel to use the Windows clipboard. You are forcing it to Select ranges, which redraws the screen. You are forcing it to calculate the “last row” twice for every single file.

This cell-by-cell operation is the primary reason a VBA macro is slow. You are literally doing the manual process, just with code.

Bottleneck #3: The “Brittle” Factor (It’s Built to Break)

Let’s say you built your script, and it finally works. It takes 45 minutes, but it runs. You’re a hero.

Until next month.

On Monday, the Sales team sends their file. But they added a “Region” column. Your script was built to copy Range("A2:Z1000"). But now the data goes to AA1000. Your macro runs, doesn’t warn you, and silently cuts off the last column of data.

Or, a different team renames the “Sales” tab to “Sales_Oct.” Your macro tries to open wb.Sheets(1)… but Sheet1 is now a blank default sheet. Your macro happily copies nothing and you get a blank row in your master file.

This is the fragility of a VBA merge multiple excel files script. It’s not a data process; it’s a dumb, fragile set of recorded clicks.

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The Modern Fix: Python & Pandas (The “Factory” Method)

So, if VBA is the slow “robot arm,” what’s the alternative? It’s Python, using its data-analysis library, Pandas.

Let’s reframe the problem. You don’t want to “open, copy, and paste.” That’s just the Excel way of doing it.

Your actual goal is to:

1. Read the data from 50 files.
2. Stack them all into one big table.
3. Save that one big table as a new file.

This is what Python was born to do. It doesn’t use a “robot arm.” It uses a “factory.”

How Python Merges 50 Files (The 5-Line Solution)

Here is the entire Python script to solve your problem. This is the real code.

import pandas as pd

import glob

# 1. Get a list of all Excel files in the folder

# The * wildcard means “find any file that ends in .xlsx”

all_files = glob.glob(“C:/My_Reports/*.xlsx”)

# 2. Create an empty list to hold all our data

list_of_data = []

# 3. Loop through the list of files, read them, and add to our list

for file in all_files:

df = pd.read_excel(file)

list_of_data.append(df)

# 4. Stack all 20 data tables into ONE, at the same time

master_df = pd.concat(list_of_data)

# 5. Save the final file ONE time.

master_df.to_excel(“Master_Report.xlsx”, index=False)

That’s it. You’re done.

Why is This 100x Faster Than VBA?

Let’s look at what this script is doing differently.

1. No “Opening” Excel:

pd.read_excel(file) does not open the Excel application. It doesn’t load the ribbon, the fonts, or the buttons. It just uses a lightweight reader to go into the file, find the raw data, and pull it directly into memory. This is thousands of times faster than Workbooks.Open.

2. No “Copy/Paste”:

The script never touches your clipboard. It’s not pasting anything. The pd.concat(list_of_data) command is a high-speed, in-memory operation. It’s like taking 50 stacks of paper and instantly combining them into one tall stack. There is no cell-by-cell looping.

3. It’s Robust, Not Brittle:

What happens if the Sales team adds a “Region” column?

• VBA: Fails.
• Python: It just works. The pd.concat command is smart. It will “align” the headers. It will see the “Region” column and just add it. It will see the other files don’t have that column and will simply fill in “null” for those rows. The script doesn’t break. In fact, it correctly handles the new data without you changing a single line of code.

This is the difference between a 30-year-old macro and a modern data tool.

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A Head-to-Head Comparison: VBA Merge Multiple Excel Files vs. Python

Let’s put them side-by-side.

Feature	The VBA merge multiple excel files Script	The Python “Factory” Script
The Core Logic	Cell.Copy $\rightarrow$ Sheet.Paste (Cell-by-Cell)	pd.read_excel $\rightarrow$ pd.concat (In-Memory)
Speed (50 Files)	20 – 45 Minutes (or crashes)	30 – 90 Seconds
Scalability	Fails on large files. VBA macro is slow and gets exponentially slower with each new file.	Scales perfectly. Can merge 500 files almost as easily as 50.
Robustness	Extremely Brittle. Breaks if a column name, tab name, or file name changes.	Extremely Robust. It matches headers, so it doesn’t break if columns are reordered or added.
Error Handling	Fails with cryptic pop-ups (Run-time error '9').	Provides clear, readable error messages (FileNotFoundError: 'Report.xlsx').
Readability	50+ lines of complex, nested code. Hard to read, hard to maintain.	~5-10 lines of logical, readable code. Easy to understand and edit.

You Don’t Have a “VBA” Problem. You Have a “Tool” Problem.

You came here looking for a better VBA merge multiple excel files script. But the truth is, you’re just looking for a better tool.

Relying on VBA for heavy data processing in 2026 is like trying to win a Formula 1 race with a horse and buggy. It doesn’t matter how well you whip the horse—it’s just not the right machine for the job.

You’ve already outgrown macros. You’re a power user who is hitting the absolute limit of what Excel was designed to do.

The best part is, you don’t have to abandon the tool you love. The best workflow still ends in Excel.

The modern “Frustrated Excel Lover” workflow is:

1. Use Python: Run a simple, fast Python script to do all the heavy, repetitive work—the merging, the cleaning, the processing.
2. Save to Excel: The last line of your script saves one, final, perfectly clean Master_Report.xlsx file.
3. Use Excel: You open that one clean file (which is now small and fast) and do the fun part: build your PivotTables, make your charts, and find the insights.

You’re not replacing Excel. You’re just replacing the worst, most painful 10 hours of your month with a 10-second script.

You don’t need a better macro. You need a better engine.