Aspirin

Leveraging order data to suggest optimal purchase patterns, to predict the orders a wholesaler will make in the next month, and to predict margin of time before expiry on orders

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The Problem

Products that expire before being consumed must be destroyed Significant source of waste

Our Solutions

  • Leveraging order data to suggest optimal purchase patterns
  • Leveraging order data to predict the orders a wholesaler will make in the next month
  • Leveraging order data to predict margin of time before expiry on orders

Optimal Purchase Patterns

  • How to improve efficiency of orders from wholesalers?
  • Many wholesalers order the same item multiple times per week — identify and combine into larger orders.
  • Can set desired order frequency (ie. monthly) and prioritize wholesalers and products to focus on

Combining Shipements

  • Across different products, which shipments could be combined?
  • We developed a method to identify clusters of products where purchases are correlated but shipped separately
  • For each wholesaler, we Identify opportunities for combining orders and reducing the number of total shipments

Models

  • Random Forest
  • Linear (Lasso) Regression

Results

  • Average r-squared score for linear regression 0.87/1.00
  • Some features are more important than others

Conclusions

Conclusions from expiry margin prediction problem:

  • Develop drugs with longer expiry dates!
  • Some (anonymized) molecules and products seem to have problems in the supply chain (Ask us about which ones!)

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