New Leaf AnalyticsHR & Workforce Intelligence
NEW LEAF ANALYTICS|Industrial-Organizational Intelligence

Automate the Busywork. Empower Your People.

We build you automated systems that empower your workforce.

Core Capabilities

Where We Can Start

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SERVICE 01Statistical Modeling

Predictive Turnover & Retention Diagnostics

We aggregate and clean your historical employee data to identify the exact variables driving employee churn. By pairing HRIS records with randomized pulse surveys, we build early-warning models before resignations hit.

Logistic RegressionCross-Validation TestingRoot-Cause Attribution
Simulated Research Case Study

Modeling the Promotion Attrition Paradox using simulated data based on I/O literature.

Read Study →
SERVICE 02ETL & BigQuery

Automated HR Data Warehousing

Consolidate ATS (Lever, Greenhouse), Payroll (ADP, Gusto), and performance tools into a single, automated Google BigQuery warehouse. Zero manual CSV exports.

SERVICE 03Automated Systems

Intelligent Evaluation Systems

Replace subjective, bottlenecked annual reviews with continuous automated evaluations. Deployed systems project hundreds of hours in management time saved each year.

SERVICE 04Foundations

Ground-Zero Data Housing & Compliance

Starting with no HR tech stack? No problem. For organizations currently tracking staff on paper or fragmented local folders, we build scalable templates—from automated Google Workspace frameworks to secure relational SQL databases.

Start From ScratchCustomized to your current team size & budget.
Ian Blad — HR Analytics Consultant
About The Principal Consultant

Ian Blad

I am an Industrial-Organizational Analytics Consultant and PhD Researcher with an emphasis in organizational psychology at Seattle Pacific University. My mission is to replace workplace guesswork with empirical measurement.

Prior to launching New Leaf Analytics, I served as HR Analyst for HydroMax USA, where I architected automated evaluation systems and led turnover diagnostics. My background combines deep statistical rigor (R, Python, SQL, predictive modeling) with foundational principles in human motivation and leadership structure.

13%
Turnover Driver Isolated

Pinpointed a single latent variable causing voluntary attrition for a recent client.

100s
Management Hours Saved

Yearly savings generated by replacing manual reviews with automated evaluation pipelines.

Next Steps

Start with your current systems.

Every organization faces unique retention and operational hurdles. Schedule a focused 30-minute discovery session to audit your data flow and identify immediate ROI opportunities.