MICHAEL P. GIBB, PH.D. · CHICAGO
Statistical rigor, technical leadership and a clear commercial question. I connect analytical work to decisions about customers, revenue and the operations that support them.
Explore the researchLEADERSHIP FOUNDATION
My background spans enterprise analytics, applied machine learning and technical program leadership. I lead analytical teams and technical programs that connect statistical work to organizational priorities.
Applied multivariate statistics
Connect methods, people and operational priorities
Guide analytical work in complex organizations
COMMERCIAL RESEARCH
One evaluated synthetic demonstration and three defined research directions. These are portfolio studies, not claims of delivered client results.
01 / FLAGSHIP · MARKETING EFFECTIVENESS
A randomized campaign study connects incremental contribution, uncertainty and the cost of a decision. Evaluated on synthetic customers with known ground truth.
Evaluated synthetic demonstration
SYNTHETIC EXPERIMENT · 6,000 CUSTOMERS
$8.16Estimated incremental contribution per customer
95% interval: $6.36–$9.95
Known simulated effect: $8.00. Not actual business impact.
SALES · REVENUE OPERATIONS
Estimate conversion, timing and revenue uncertainty using only information available at the forecast date.
Planned research
View research design ↗CUSTOMERS · RETENTION & VALUE
Separate attrition prediction from evidence that a retention action changes behavior or creates value.
Planned research
View research design ↗OPERATIONS · DEMAND & CAPACITY
Connect demand forecasts to staffing, inventory or service-capacity choices with explicit constraints and decision costs.
Planned research
View research design ↗HOW I APPROACH THE WORK
Connect marketing effectiveness and customer acquisition, sales forecasts, retention or capacity planning to a concrete decision, owner and evaluation criterion.
Distinguish prediction from causation. Compare practical baselines, preserve information available at decision time, and quantify the uncertainty that matters.
Make assumptions and limitations legible. Apply AI and machine learning where they improve the work, with human judgment, reproducibility and clear accountability.
LET’S CONNECT
Director / VP opportunities in analytics, AI, data science and technical leadership.