McKesson used an OR scenario model, freeing over $1B of committed capital.

McKesson runs a huge, complex pharmaceutical supply chain where policy choices are hard to see and expensive to reverse.

The usual answer is to improve each supply-chain function separately. IBM Research instead built the Supply Chain Scenario Modeler, a tool that optimises the distribution network, supply flow, inventory and transportation policies together.

The critical move was wiring the OR models to a bank of quantified impacts, including a structured data model that links results directly to a profit-and-loss statement by product category, so executives could see the dollars behind a policy choice.

Since the work began in 2009, McKesson's Pharmaceutical division reduced its committed capital by more than $1 billion, and the modeling spawned a roadmap of further improvement projects.

Model the chain and wire it to the P&L

Pharmaceutical supply chains span many paths and products, so a whole-chain model is needed

Tying OR results to P&L by category makes the trade-offs legible to executives

Scenario modeling lets McKesson test policy changes before committing capital

A structured data model amplified the value into further projects

To make OR change executive behaviour, connect the model's output to the financials you already report on, not just to a KPI.

Since 2009, McKesson's Pharmaceutical division reduced its committed capital by more than $1 billion. The model also generated a roadmap of quantified opportunities, including a new air-freight supply-chain path, and became a 2013 Edelman finalist.