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Create CVApplicant Tracking Systems do not “see” columns. They convert documents into linear text streams. When a two column resume is uploaded, the ATS attempts to extract text in reading order based on its parsing engine.
The problem is structural sequencing.
Most ATS platforms:
In a two column resume, content from the right column is often interwoven into the left column during extraction. The result is fragmented data that does not map cleanly to experience, skills, or education fields.
The system does not evaluate visual clarity. It evaluates structured extractability.
The failure is not universal, but it is common under these conditions:
If the left column contains Experience and the right column contains Skills, the ATS may extract text like this:
Experience
Company A
Skills
Python
Role description
SQL
Date
The mixing disrupts:
When job titles are not cleanly associated with dates and employer names, the ATS cannot calculate duration or seniority.
Many two column resumes place the following in a narrow sidebar:
Left Column:
Professional Experience
Software Engineer – 2020–2024
Built APIs using Python
Right Column:
Skills
Python
AWS
SQL
Common ATS Extraction Result:
Professional Experience Software Engineer – 2020–2024 Built APIs using Python Skills Python AWS SQL
Why this creates risk:
Professional Experience
Software Engineer
2020–2024
Skills
Python
AWS
SQL
Why this performs better:
During parsing, sidebar content may be:
If critical keywords are lost or misplaced, Boolean filters fail.
ATS systems rely on recognizable section headers such as:
When a header appears in a compressed column with altered spacing or formatting, the parser may not detect it as a structural boundary. This causes entire sections to be treated as generic text rather than categorized data.
Once categorization fails, ranking weight decreases significantly.
The difference is not visual. It is structural clarity for the parser.
Some modern ATS systems with advanced parsing engines can interpret basic two column layouts if:
However, compatibility varies by platform. Large enterprise systems often prioritize stability over advanced layout recognition, meaning they parse conservatively.
Because candidates do not control which ATS platform a company uses, structural risk increases.
Two column resumes often:
But ATS systems do not evaluate visual hierarchy. They evaluate database integrity.
If skill keywords are misparsed, ranking drops even though the resume appears optimized.
Candidates frequently assume that because the document uploads successfully, it has been correctly interpreted. Upload success does not equal structured extraction success.
It depends on:
The risk is not guaranteed failure — it is unpredictable extraction accuracy.
In automated screening environments, unpredictability reduces ranking reliability.
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