SKU Rationalization

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$B+

Annual Revenue

K+

Employees

Consumer Goods
Beauty & Personal Care

Marketing
Insights & Analytics
Product Management

ML Model Development
Predictive Analytics
Natural Language Insights

Problem

Consolidating acquisitions and global pandemic made it difficult to take effective action despite financial crunch

Innovations had to be given some runway, and brand loyalty had to be in the mix

But teams needed clear direction on which SKUs to cut, and which to drive ASAP

Thousands of SKUs required comprehensive analysis across time, geography, category, color, size and market.

Innovated a novel performance-based SKU clustering (proven by back-testing) that unlocked critical guidance

Engineered multi-dimensional analysis framework for long-range forecast of cluster and sku-level performance

Built prioritized recommendation system delivering actionable insights for each SKU, aligned to market and industry

Delivered seamless integration into financials for fast action during planning and retailer contract negotiations

Clear natural language guidance for actions related to cutting low performers or driving intervention on middling SKUs

Successfully reduced product portfolio by 40% in first year by eliminating low performing SKUs

Enabled stronger cost-savings across the business through targeted SKU optimization

Provided clear trajectory forecasts showing optimal intervention timing per SKU

Transformed product portfolio management with data-driven decisions

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