🏆 Achievement: 2nd Place out of 12 Teams
Competition: Drexel LeBow x Deloitte Datathon 2026
Date: February 6, 2026
Timeline: ONE DAY (data analysis, strategy, presentation)
Challenge: "Geographies of Risk: Where is cancer burden highest, and how can we intervene?"
The Challenge
On February 6, 2026, my team competed in the Drexel-Deloitte Datathon with a daunting task: analyze real-world public health data, identify neighborhoods where cancer burden is highest, and design evidence-based interventions—all within a single day.
We chose Question 2 from the competition brief, focusing on geographic concentrations of cancer risk in underserved communities. Our target cities: Philadelphia, PA and Chicago, IL, representing 444,000 high-risk residents across 13 priority neighborhoods.
The Problem We Uncovered
Through analysis of CDC data, Chicago Health Atlas, and Drexel Urban Health Collaborative datasets, we discovered a critical pattern: tobacco retailers concentrate disproportionately in low-income neighborhoods, creating what researchers call a "micro-environment of normalized smoking."
The numbers were stark:
- Philadelphia: 69% more tobacco retailers per capita in low-income areas
- Philadelphia: 90% of schools within 1,000 feet of a tobacco retailer
- Chicago South Side: 2× cancer death rate vs. national average (644 vs. 320 per 100,000)
- Youth impact: 13% higher tobacco use in high-density areas
Tobacco drives 30% of all cancer deaths, making retail density a modifiable environmental factor with massive potential impact.
🎯 Key Takeaways (Preview)
Some early reflections from the competition:
- The importance of rapid exploratory data analysis to identify patterns quickly
- Balancing model sophistication with interpretability for stakeholder presentations
- Effective team coordination strategies for distributed analytical work
- How domain knowledge in supply chain/logistics informed our modeling choices
Our Solution: Three-Tier Strategic Approach
Tier 1: Licensing Cap Policy
Chicago Implementation (replicating proven Philadelphia model)
- Cap tobacco retailers at 1 per 1,000 residents
- Evidence: Philadelphia's 2016 policy achieved 20.3% density reduction in 3 years
- Greater reduction in low-income districts (equity improvement)
- Validated by CDC REACH study with control cities
Tier 2: Enhanced School Buffer Zones
- Philadelphia: Expand from 500 feet → 1,000 feet
- Chicago: Expand from 100 feet → 600 feet
- Reduces youth exposure during critical developmental years
- Philadelphia achieved 12% fewer retailers near schools with existing 500-foot buffer
Tier 3: Health System-Funded Buyback Program (Our Innovation)
💡 First-in-Nation Solution
The Problem with Traditional Policy: Political resistance from retailers and concerns about economic impact make mandates difficult.
Our Innovation: Voluntary health system-funded buyback program
How It Works:
- Health systems invest $10M ($5M per city)
- Buy out 200-275 retailers in oversaturated neighborhoods
- Offer $30K-$250K per retailer (1-2× annual tobacco revenue)
- Voluntary license surrender (politically viable)
Why It's Genius:
- Hospitals capture $300-400M in avoided cancer treatment costs
- ROI: 30-40:1 for health systems
- Leverages existing $150B hospital community benefit funds
- Precedent: Federal tobacco buyout (2005-2014) paid $10B to farmers, 95% participation
- Aligned incentives: Capitalist solution meets public health need
Expected Outcomes & Timeline
Years 1-3: Immediate Density Reduction
- 15-20% retailer density reduction
- 200-275 voluntary buyouts completed
- Policy infrastructure established
Years 3-7: Behavioral Impact
- 10-15% reduction in youth tobacco initiation
- 5-8% reduction in adult smoking rates
- Community norm shift begins
Years 10-20: Screening & Prevention
- 25-35% increase in lung cancer screening in target areas
- Early detection rates improve
- Cancer mortality begins declining
Years 20-30: Long-Term Health Impact
- 10-15% lung cancer incidence reduction
- $555M total value generated
- 2,000+ prevented smokers
- Health equity gap narrows
Return on Investment
Investment Required:
- Buyback Program: $10M ($5M Philadelphia + $5M Chicago)
- Policy Implementation: $4M (3-year enforcement, community engagement)
- Total Investment: $14.4M
Value Generated (20-30 years):
- Smoking prevention: 2,000 prevented smokers × $200K lifetime costs = $400M
- Early vs. late stage detection: $75M savings
- Avoided cancer cases: $80M savings
- Total Value: $555M
📊 Net ROI: 38:1
For every dollar invested, we generate $38 in long-term value. This isn't just good public health—it's a sound financial investment.
Data Sources & Methodology
Primary Data Sources
- Cancer Data: CDC U.S. Cancer Statistics (USCS) 2000-2021, Chicago Health Atlas, Drexel Urban Health Collaborative
- Tobacco Retail Data: Philadelphia CHART (October 2024), CDC REACH 2020, ASPiRE 30-city analysis
- Policy Evidence: Morrison et al. (2020) American Journal of Public Health - Philadelphia licensing cap validation
- Cost Data: UDS Health 2025, hospital financial data, Federal tobacco buyout program precedent
Analytical Approach
- Spatial analysis: Retailer density mapping by census tract
- Equity analysis: Income-based disparity quantification
- Comparative analysis: Philadelphia vs. Chicago policy environments
- Outcome modeling: Evidence-based projections from Philadelphia results
What Made This Creative
1. First-in-Nation Innovation
No U.S. city has implemented a health system-funded tobacco retailer buyback program. We broke new ground while building on proven policy foundations.
2. Aligned Incentives
Capitalist solution (ROI-driven) meets public health need. Health systems invest in prevention to capture long-term savings from avoided treatment costs.
3. Political Viability
Voluntary mechanism solves political resistance. Fair transition support (not punishment) makes implementation feasible where mandates fail.
4. Leverages Existing Resources
Redirects $150B annual hospital community benefit spending toward measurable prevention with quantifiable outcomes.
5. Evidence-Based Foundation
Built on Philadelphia's proven success (CDC validated), not theoretical models. Replicable, scalable, and measurable.
Team & Collaboration
Our team of 5 brought diverse expertise:
- Public Health Data Analysis: Multi-source data synthesis
- Policy Analysis: Comparative effectiveness research
- Financial Modeling: ROI calculations, long-term projections
- Strategic Communication: Complex information → clear narrative
My Role: I coordinated parallel workstreams, synthesized findings into coherent strategy, and ensured our solution balanced feasibility with impact. Under extreme time pressure, I applied program management principles: scope definition, resource allocation, risk identification, and stakeholder alignment.
Key Learnings
Skills Applied
- Synthesis Under Pressure: Complex data → actionable insights in hours
- Cross-Functional Collaboration: Parallel workstreams coordinated effectively
- Evidence-Based Decision Making: Grounded creativity in proven outcomes
- Stakeholder Alignment: Balanced health systems, retailers, community needs
- Communication Excellence: Technical rigor translated for non-technical audience
Program Management Parallels
This experience mirrors core PM competencies:
- Scope Management: Defined problem boundaries within time constraints
- Resource Allocation: Divided team across workstreams strategically
- Risk Management: Identified political barriers, designed around them
- Quality Delivery: Maintained analytical rigor despite time pressure
💭 Personal Reflection
"This datathon reinforced exactly why I'm passionate about program management: the ability to synthesize complex information, lead cross-functional collaboration, and deliver measurable results under tight deadlines. When data meets creativity and stakeholder alignment, you can design solutions that work both on paper and in practice."
Judge Feedback
"Impressed by the depth and creativity achieved in such a compressed timeframe. The health system-funded buyback program represents a genuinely novel approach to a persistent public health challenge."
—Deloitte Datathon 2026 Judges
Connection to Career Goals
This datathon reinforced my passion for program management at the intersection of technology, data, and social impact:
- Data-Driven Decision Making: Leveraging analytics to inform strategy (parallel to AI/XR product development)
- Cross-Functional Leadership: Coordinating diverse expertise toward unified outcome
- Tight Deadline Delivery: Executing under pressure with quality (tech product cycles)
- Innovation Within Constraints: Creative solutions within political/financial realities
- Measurable Impact: Quantifying outcomes to demonstrate value (key for tech ROI)
Transferable Skills for Tech Industry
- AI/ML Product Management: Evidence-based feature prioritization, outcome modeling
- XR/AR Implementation: Stakeholder alignment, implementation feasibility analysis
- Digital Transformation: Change management, incentive alignment, adoption strategies
- Healthcare Tech: Understanding complex systems, regulatory navigation, ROI demonstration
Project Impact
Geographic Scope: 444,000 residents across Philadelphia & Chicago
Projected Value: $555M over 20-30 years
Innovation Level: First-in-nation health system-funded buyback program
Recognition: 2nd Place, Deloitte Datathon 2026