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Chapter 13: Data Science & Business Strategy (Superior Data Scientists…
Chapter 13: Data Science & Business Strategy
Thinking Data-Analytically
Managers
Must understand fundamental principles
Willing to invest in data and experimentation
Data scientists struggle with investment in proper training
Ask question of a data scientist
Management Team
Must have seasoned data scientist
Needs to be diverse
We can't expect manager to have deep expertise in data science and vice versa
Involves collaboration between data scientists and managers
Achieving Competitive Advantage with Data Science
Data & data science are strategic assets
Asset needs to be of value to firm
Value of asset depends on other strategic decisions
Dell & Compaq Example
Dell: Direct to Customer
Compaq: Retail outlets
Amazon vs. Borders Example
Amazon used data to recommend books
Borders not able to exploit data on who bought what
Sustaining Competitive Advantage with Data Science
Competitors duplicating assets
Competitors may surpass us if they have greater resources
Always stay one step ahead
Always invest in new data assets
Always develop new techniques and capabilities
Having a great team will keep you ahead of the game
Formidable Historical Advantage
Historical circumstances = advantageous
Costly for other competitors to catch up
Example: Amazon - amass tremendous data assets in the "Dotcom Boom"
Allow them to create valuable data-based products
Data products can increase the cost to competitors replicating data asset
Switching costs: competitors would have to provide extra value to Amazon's customers to entice them.
Unique Intellectual Property
Can include
Techniques for mining the data
Techniques for using the results
Can be patented or just trade secrets
Patent: Competitor will be unable to duplicate or will have an increased expense
Trade secret: competitor does not know how solution is implemented
Unique Intangible Collateral
Such as
Company Culture: example - a culture that embraces experimentation will be an easier place for data science
Superior Data Scientists
Some individuals have the combination of innate creativity, analytical acumen, business sense, and perserverance
Top-notch data scientists in high demand
Company that has built a strong data science capability have a substantial and sustained advantage
Superior Data Science Management
Managers
Need to truly understand needs of the business
Need to understand fundamentals
Need to be able to communicate well
Need to coordinate technically complex activities: integration of multiple models and procedures
Need to be able to anticipate outcomes of data science projects
Attracting and Nurturing Data Scientists and Their Teams
Firms must create a culture where data science and scientists can thrive