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CH13: Data Science and Business Strategy (Nurturing Data Science (Give…
CH13: Data Science and Business Strategy
Mindsets
Managers
Distribute correct resources
Collaborate
Strategic Implications
Undervalues Predictive Modeling
Data Scientists
Technical Details
Values Predictive Modeling
Competitive Advantage
Complimentary Assetts
Must be Valuable
Must be Rare
Sustaining Competitive Advantage
Continuous Investment
Capability Development
Expense of Replicating
Historical Learning Curve
Patents & Trade Secrets
Intangible Assets
Superior Data Scientists
Superior Data Management
Translating Jargon
Anticipate Business Needs
Integrate Models with Costs
Prior Success
Reputation
Competitive Disadvantage
Nurturing Data Science
Give Responsibility
Advocate Publishing & Sharing
Combine Money, Data, Interesting Problem
Hire Advisors
Hire Third Parties
Understand the Fundamentals
Read Case Studies
Formulate Case Studies
Integrate Problem w/ Data
Interact w/ Employees
Formulating & Evaluating
Is the business problem well specified?
Is it clear how we would evaluate a solution?
Will we have evidence of success before making a huge investment in deployment?
Does the firm have the assets it needs?
Big Red Proposal Example
Business Understanding
Migration Time Inperceise
Poor Alignment
Data Understanding
No Labels for Examples
No Control Group
Modeling
Classification Better Choice
Evaluation
No Holdout Approach
Cross Validation
Staged
Deployment
Random Selection Poorly Considdered
Does Regression score of .5 respond to probability of migration of .5?
.5 is Arbitrary
No Use of Ranking
Self Assessment
Immature
Ad hoc
Little Understanding
Medium
Well Trained
Links problems with data science
High
Invest in Process
Open Minds