Workforce Analytics Benchmarking: Building an Automated Pipeline for HR Analysis
Built an automated data-cleaning workflow and led ongoing analysis of how AI is reshaping HR functions in mid-cap US tech.
Parthsarthi Varma
Analyst 2 at L.E.K. Consulting
From their time as
Analyst 2
L.E.K. Consulting • 2025
Overview
Parthsarthi has been running a workforce analytics benchmarking project at L.E.K. across multiple engagements. The work involves pulling raw LinkedIn profile data for employees across mid-cap US tech companies, then running a structured analysis to assess how HR functions are evolving.
The Story
Parthsarthi has been running a workforce analytics benchmarking project at L.E.K. across multiple engagements. The work involves pulling raw LinkedIn profile data for employees across mid-cap US tech companies, then running a structured analysis to assess how HR functions are evolving.
He built an automated data-cleaning workflow to consolidate raw position-level records into a structured dataset. The pipeline handles functional tagging, sub-function splits, attrition rates, recruiter headcount, and geographic footprint, turning messy raw data into a format ready for benchmarking analysis.
The live project he is currently running focuses on how AI and post-COVID hiring normalization are reshaping HR sub-functions. He tracks metrics including hiring velocity, functional mix shifts, and the relative impact of AI on different HR roles. He presents findings directly to his principal in regular cadences, fielding clarifying questions on why specific numbers move in particular years and defending the analytical logic behind each finding.
One recurring challenge in these cadences is compression: translating hours of data work into a clear, defensible pitch that holds up to real-time questioning without losing the nuance behind the numbers.