Common Resume Parsing Errors and Fixes: Why ATS Reads Your Resume Wrong

I recently reviewed a resume for a senior product manager who had applied to 40 roles and received zero callbacks. When I ran her beautifully designed document through a standard parsing tool, her 10 years of experience rendered as a single, garbled block of text, meaning every Applicant Tracking System (ATS) had essentially seen a blank page. If you are not getting interviews, your problem might not be your qualifications—it is likely how a machine is reading your file.

As a career coach, I spend a significant amount of time diagnosing why highly qualified candidates get auto-rejected. Nine times out of ten, the culprit is not a lack of skills. It is a failure to understand how resume parsing actually works.

Here is a look under the hood at the most common resume parsing errors, the mechanics of why they happen, and exactly how to fix them.

The Mechanical Reality of ATS Parsing

To fix resume parsing errors, you first need to understand what ATS parsing actually is. Candidates often imagine an advanced AI reading their resume the way a human would—making inferences, understanding context, and appreciating a clean visual hierarchy.

That is not what is happening.

Systems like Workday, Taleo, iCIMS, Greenhouse, and Lever use parsing algorithms that are fundamentally text-extraction and mapping tools. Their job is to strip away all your formatting, extract the raw text, and categorize that text into specific database fields: First Name, Last Name, Email, Phone, Employer, Job Title, Dates of Employment, and Skills.

When a recruiter opens your profile in Workday, they often do not see your actual document first. They see the digital profile the ATS built from your document. If the parser cannot map your text to its database fields correctly, your digital profile will be blank, scrambled, or incomplete. You are effectively removing yourself from the candidate pool before a human ever sees your name.

The Two-Column Trap: Why Modern Designs Fail

If you bought a modern resume template off Etsy, there is a high probability it features a two-column layout. Usually, contact info and skills sit in a narrow left column, while professional experience takes up the wider right column.

To a human, this looks efficient. To an ATS, it is a disaster.

How the Parser Reads Columns

Most ATS parsing algorithms read documents the same way early computer programs read data: strictly left-to-right, top-to-bottom. They do not recognize vertical dividing lines.

If your left column lists the skill "Agile Methodology" and your right column lists the job title "Senior Project Manager" on the same horizontal plane, the parser reads straight across. It extracts your job title as: Agile Methodology Senior Project Manager.

When the system tries to search its database for candidates with "Project Manager" experience, your profile will not surface because your job title is corrupted.

The Fix: Stick to a single-column layout. If you want to save space, use tabs and right-alignment for dates and locations, but keep the core text flowing in a single vertical column.

Tables and Text Boxes: The Invisible Black Holes

Many candidates use invisible tables to align their core competencies, or insert text boxes to make a summary statement stand out.

The problem is that many older parsing algorithms (particularly in legacy enterprise systems like Taleo or older versions of iCIMS) cannot look "inside" complex formatting objects. When the text extractor hits a table, a text box, or a graphic, it often skips the object entirely.

If you put your 12 most important technical skills in a beautifully aligned three-column table, there is a very real chance the ATS will extract zero of those skills.

The Fix: Remove all tables, text boxes, and graphics. Use standard tabs and bullet points to align your text.

Header and Footer Nightmares

It is standard practice in Microsoft Word to put your name, email, phone number, and LinkedIn URL in the document header to save space on the page.

However, applicant tracking systems are programmed to parse the body of a document. Document headers and footers are typically treated as background metadata (like page numbers or document titles) and are frequently ignored by parsing algorithms.

I have seen countless candidates get auto-rejected simply because the ATS parsed their resume, found no contact information in the body text, and flagged the profile as incomplete.

The Fix: Keep all your contact information in the main body of the document, right at the top of page one. Never use Word's built-in Header or Footer function for anything other than page numbers.

Date Formatting: The Experience Calculator Killer

When you apply for a job that requires "5+ years of experience," the ATS does not just look for the number 5. It uses an internal experience calculator to add up the dates attached to your job titles.

If it cannot understand your date formatting, it calculates your years of experience as zero.

Common resume formatting mistakes include:

• Using only years (e.g., 2020 - 2023). The system doesn't know if this is 25 months or 47 months.
• Using non-standard terms (e.g., "Fall 2021" or "Graduation to Present").
• Placing dates far away from the job title, causing the parser to associate the date with the wrong role.

The Optimal Date Format

Parsers are programmed to look for standard date arrays.

The Fix: Always use the Month Year - Month Year format. You can spell out the month or use numbers, but be consistent.

• Correct: March 2019 – August 2023
• Correct: