An anonymous research project mapping how ATS systems and recruiters actually screen Business Analysts, Data Analysts, and Project Managers.
Run by KAtlas Analysis. Every contributor receives the aggregated findings report and an invitation to a private sector briefing.
Most career advice for Business Analysts, Data Analysts, and Project Managers is based on what candidates assume hiring managers want. We are building something different: a pattern library derived from what recruiters and hiring managers actually observe, across real ATS systems, real screening decisions, and real rejection signals that candidates never see.
Eight to ten minutes of your time. Eighteen questions covering how your ATS classifies candidates, which fields carry the most algorithmic weight, what causes strong candidates to be filtered before human review, and how you handle career pivoters and adjacent-experience hires. All responses are anonymous. No company names are collected. You respond by sector only.
Every contributor receives the full aggregated findings report when the dataset is complete. You will also receive an invitation to a private 30-minute briefing where we present the key patterns and how they compare across sectors. If your screening environment produces outcomes that differ significantly from sector averages, that is useful information for your own process.
Recruiters, talent acquisition leads, and hiring managers who screen for BA, DA, PM, Product, or Programme Manager roles. Enterprise ATS environments (Workday, Greenhouse, Lever, SuccessFactors, Taleo) produce the most structurally useful data, but all screening contexts are valuable. If you make or influence hiring decisions in these role families, your input belongs in this dataset.
KAtlas delivers Strategic Dossiers to BA, DA, and PM candidates. The diagnostic quality of those dossiers depends on having real data from both sides of the hiring table. The candidate data already exists. The recruiter side is what we are building now.
All responses are aggregated and analysed as a dataset. No individual response is identified, attributed, or shared. The findings are published as sector-level patterns only. Respondents receive the full aggregated report before public release.
If you screen for BA, DA, PM, Product, or Programme Manager roles, your input belongs in this dataset.
Access the Study →Run by Nikhil Sharma · KAtlas Analysis · Company No. 16186473