Enterprise-Level Data Science Success
summary
Defines success as effort to output to decisions to actions to measurable outcomes, and stresses growing analytics maturity and decision maturity together. Uses R and Python in a Fortune 500 supply chain context to move from models to business KPIs. Recommends shifting teams from a pressure to opportunity mindset, building equal partnership with stakeholders, and anticipates harsh human judgment illustrated by a pricing example where the model suggests $0.90 -> $0.95 realized in negotiation.
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