kimberly clarke problem statement

Inspiration

We were inspired by Kimberly-Clark's strategic vision to expand sustainably into new markets. The goal of optimizing logistics and operations drove us to leverage demographic insights and geographic analysis to guide facility placement decisions.

What it does

Our project identifies the optimal locations for three new tissue mills by combining U.S. Census demographic data with advanced logistics modeling. It provides clear, actionable insights to minimize transportation costs, maximize market coverage, and enhance sustainability.

How we built it

We integrated publicly available U.S. Census datasets with logistics cost estimates from AAA and transportation networks data from federal sources. Data was cleaned and aggregated in excel, visualized using interactive dashboards, and strategically analyzed at state level.

Challenges we ran into

Key challenges included handling large datasets with differing granularities, accurately estimating transportation costs dynamically from external sources, and translating complex geographic insights into straightforward recommendations for C-level stakeholders.

Accomplishments that we're proud of

We successfully delivered a user-friendly dashboard providing strategic clarity for executives. Our recommendations effectively balance sustainability considerations, and cost efficiencies, enabling data-driven location decisions with confidence.

What we learned

We learned to handle and integrate large, diverse datasets, improved our skills in geographic data visualization and logistical modeling, and gained valuable insights into strategic decision-making processes in manufacturing and supply chain planning.

What's next for kimberly clarke problem statement

Future work includes incorporating real-time logistics cost updates, refining our predictive models with more granular consumer demand data, and continuously monitoring market shifts to ensure ongoing strategic optimization and operational efficiency.

Built With

• bi
• power