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Implementing AI for
New Business Models
and Efficiencies
Parag Shrivastava
Senior Director, Enterprise Data Architecture
McKesson Corporation
1
2
Data Story?
About McKesson
Corporation*
3* Source: Investor Presentation| J.P. Morgan Healthcare Conference | Jan 8th 2019
AI brings strong total
opportunity case
It enables both, new revenue, and cost savings
CUSTOMER
FOCUS
4
Customer focus
increases relevance
5
Belongingness
Freedom
Business to Consumer/ PatientBusiness to Business
Growth Costs
Growth Business Use
Cases
AI enables new models of engaging consumers
6
Pharmacy
Omnichannel experiences
Product Planning
Clinical Decision Support
Framework for AI
Build AI solutions – lessons learned
7
Models AdoptionData Use Cases
Pilot
Ops Integration
Data Hygiene
Data Integration
Executive Buy-in
Value Driven
Iterative
Incremental win
Summary
8
Business Areas
Sample Optimization/ Use
Cases
Lessons Learned Model Development
• Procurement
• Inventory
• Distribution
• Patient Retail
• Cost Optimizations
• Reducing Returns
• Shipping and Tracking
• Patient Engagement
• Data Hygiene
• Data Rights
• Data Security
• Large Data
• Exploratory Data Analysis -EDA
• Data Tagging
• Generalized Linear Models,
Clustering, Cross Validation,
Model Optimizations
• Ideation
• Business Engagement
• Prototyping • Using Python
• Automation
• Other tools
• Models
• Pipelines
• Reusable models for tagging,
matching
Pharmaceutical Clinical Medical Surgical
KeyOutputsServicesProducts
Thank you!
Q & A
parag.shrivastava@mckesson.com
9

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"Implementing AI for New Business Models and Efficiencies" - Parag Shrivastava, Mckesson

  • 1. Implementing AI for New Business Models and Efficiencies Parag Shrivastava Senior Director, Enterprise Data Architecture McKesson Corporation 1
  • 3. About McKesson Corporation* 3* Source: Investor Presentation| J.P. Morgan Healthcare Conference | Jan 8th 2019
  • 4. AI brings strong total opportunity case It enables both, new revenue, and cost savings CUSTOMER FOCUS 4
  • 5. Customer focus increases relevance 5 Belongingness Freedom Business to Consumer/ PatientBusiness to Business Growth Costs
  • 6. Growth Business Use Cases AI enables new models of engaging consumers 6 Pharmacy Omnichannel experiences Product Planning Clinical Decision Support
  • 7. Framework for AI Build AI solutions – lessons learned 7 Models AdoptionData Use Cases Pilot Ops Integration Data Hygiene Data Integration Executive Buy-in Value Driven Iterative Incremental win
  • 8. Summary 8 Business Areas Sample Optimization/ Use Cases Lessons Learned Model Development • Procurement • Inventory • Distribution • Patient Retail • Cost Optimizations • Reducing Returns • Shipping and Tracking • Patient Engagement • Data Hygiene • Data Rights • Data Security • Large Data • Exploratory Data Analysis -EDA • Data Tagging • Generalized Linear Models, Clustering, Cross Validation, Model Optimizations • Ideation • Business Engagement • Prototyping • Using Python • Automation • Other tools • Models • Pipelines • Reusable models for tagging, matching Pharmaceutical Clinical Medical Surgical KeyOutputsServicesProducts
  • 9. Thank you! Q & A parag.shrivastava@mckesson.com 9