Data Science and Business Strategy: Chapter 13 (Data Science and Data…
Data Science and Business Strategy: Chapter 13
Competitive Advantage Using Data Science
Data science capability as an asset
Dell vs Compaq
Customers' personal needs and liking
Distribution channels using web systems
Decide whether at disadvantage
Adoption of strategies
Always keep one step ahead of competition
Invest in new data assets
Utilize competitors' inability to replicate
Unique intellectual Property
Data Science and Data Scientists
Data mining competition
Best scientists in world compete in this competition
Variety in ability of the best
High demand for high skilled
Using experience is the best learning mechanism
Strong professional network
"Jack of All Trades"
Data Science Management
A good manager must
Truly understand and appreciate needs of busienss
Anticipate needs of business
Interact with counter parts
Translate data science jargon
Coordinate technical activities
Understand technological architectures
Anticipate outcomes of data science projects
Firm's management must think data-analytically
Firm's management must create where data science will thrive
Accept Creative Ideas from Any Source
Can come from any direction
Executives examining new lines
Directors dealign iwth profit and loss
Managers looking at business process
Employees with knowledge of how a particular process functions
Data that might help manager directly
Formulate solid proposals
Is problem well specified?
Does data science solution solve problem?
Is solution evaluation clear?
Can we see evidence of Success before an investment?
Does firm have data assets it needs?