All case studies
PepsiCo
Celsius Distribution Network
A cost-efficient supply chain model for Celsius beverages post-acquisition, modeled end-to-end in Excel. Evaluating demand forecasts, $21M startup capital allocation, capacity constraints, and sourcing trade-offs to maximize long-term profitability
- When
- January – May 2026
- My role
- Team of 5 · Demand Forecasting and Financial Projection
- Discipline
- Network design
$20MProjected Profitability
Situation
PepsiCo acquired exclusive Midwest distribution rights for Celsius but lacked specialized production infrastructure for its distinct package sizes. Tasked with investing a $21M capital budget, our team needed to build an internal/external network, balance capacity constraints across 5 product lines, and design a profitable supply chain to sustain dynamic demand over a 2-year timeline.
Analysis
- Built monthly demand forecasts across core and innovation flavors (Galaxy Vibe), incorporating seasonal variations and forecast accuracy margins (+/-5% to +/-12%).
- Evaluated capital allocation trade-offs across 3 internal production line choices ($10M–$21M) in Lafayette, IN vs. external co-packers in Champaign, IL and Cincinnati, OH.
- Modeled monthly fill rate targets (98%) to avoid severe service penalties ($300k–$600k/month) while minimizing inventory holding and handling fees at the central warehouse.
- Analyzed fleet acquisition vs. common carrier shipping options, optimizing truckload utilization (20 pallets/truckload) and trade-offs between skilled vs. unskilled labor reliability.
Outcome
- Delivered an end-to-end financial and operational model projecting $20M in profitability across the 2-year horizon while preserving capital budget flexibility.
- Structured dynamic trade-off scenarios that enabled leadership to trace profitability back to specific production, labor, and transportation inputs.
- Maintained target service fill rates (>98%) to prevent revenue loss and penalty charges while managing monthly safety stock efficiency.
Tools
- Excel modeling
- Demand forecasting
- Financial projection
- Capacity analysis
- Quantitative analysis