The $145.2M Efficiency Win

The Challenge: As General Motors transitioned to a digital-first EV fleet model, operational costs and battery health predictability emerged as critical barriers to scaling profitability for enterprise customers.

The Strategy: Engineered a suite of telemetry-based machine learning models to analyze real-time battery degradation and energy consumption across global fleet deployments. I led the "translation" of this technical telemetry into a strategic battery-sizing framework.

The Execution: Integrated ML-driven insights into the product development lifecycle, allowing for precision in capital expenditure and vehicle specifications.

The Result: Delivered $145.2M in annual operational savings and established the gold standard for EV fleet sustainability metrics within the organization.

The $325M Revenue Innovation

The Challenge: Managing billions of daily data points from connected vehicles without a clear, scalable roadmap to convert that data into recurring digital revenue.

The Strategy: Architected a comprehensive data-driven product roadmap and engineered a telematics prototype designed to identify and capture "moments of need" for global vehicle owners.

The Execution: Partnered with cross-functional product and engineering teams to build a proprietary data ecosystem that identifies high-propensity targets for subscription services.

The Result: Unlocked $325M in projected annual benefits, successfully pivoting the data department from a support function to a primary revenue driver for Global Connected Services.

Driving 33% Market Penetration

The Challenge: Stagnant growth in the adoption of digital fleet products, with market penetration hovering at 25% amidst increasing competition.

The Strategy: Conducted a deep-dive behavioral analysis of the global fleet customer base to identify friction points in the digital product journey. I redesigned the go-to-market analytics strategy to prioritize high-lifetime-value segments.

The Execution: Led a globally dispersed team of analysts to implement real-time growth tracking and predictive churn models, allowing sales teams to proactively target expansion opportunities.

The Result: Successfully scaled market penetration for Global Fleet Digital Products to 33%, significantly increasing the revenue footprint of a multi-billion dollar business unit.

Driving a 33% Expansion in Digital Product Adoption

The Challenge: A multi-billion dollar business unit faced a plateau in digital product adoption, with market penetration stalled at 25% despite significant investment in infrastructure.

The Strategy: Developed a behavioral analytics framework to identify high-friction points in the global fleet customer journey. I re-architected the go-to-market data strategy to prioritize "high-propensity" customer segments over a broad-market approach.

The Execution: Partnered with global sales leadership to deploy real-time market share tracking and automated churn-prevention triggers based on product usage telemetry.

The Result: Successfully scaled market penetration to 33% within 18 months, significantly increasing the recurring revenue footprint of the digital fleet portfolio.

Optimizing a 16+ Member Multi-Regional Analytics Unit

The Challenge: A globally dispersed analytics team (spanning multiple time zones and business units) struggled with siloed data practices and inconsistent project delivery timelines.

The Strategy: Applying Marine Corps "Commander’s Intent" principles, I redesigned the team's operational framework. I shifted the focus from "task completion" to "Mission Impact," establishing a unified set of KPIs tied directly to enterprise ROI.

The Execution: Integrated agile methodologies into the data science lifecycle and established a "Translation Layer" training program to ensure technical analysts could communicate value effectively to non-technical stakeholders.

The Result: Reduced project cycle times by 22% and increased team engagement scores to the top decile, while managing a multi-million dollar annual media and operational budget.

Shaping the Future of Business Analytics at Wayne State University

The Challenge: The gap between academic curricula and the rapidly evolving demands of the AI/ML industry was creating a "talent lag" in the enterprise workforce.

The Strategy: As an Advisory Board Member, I acted as a strategic advisor to the Graduate School of Business. I provided an "Executive View" on how GenAI, ethics, and P&L accountability must be integrated into modern analytics training.

The Execution: Chaired industry-partnership initiatives and mentored MBA candidates on executive presence, ensuring the program's output met the high-stakes requirements of Fortune 500 employers.

The Result: Enhanced program relevance, leading to a stronger pipeline of "Value-First" analysts and reinforcing my position as an industry steward and strategic governor.