What does it mean for an organization to be data-driven? It is not about having lots of reports and dashboards or big data but having the right data culture. Learn more about that culture in this executive summary of the key findings in Carl Anderson's new book "Creating a Data-Driven Organization" (2015) from O'Reilly Media.
7. a strong testing culture
Being data-driven means having…
Innovate through online and offline experimentation.
Encourage hypothesis generation broadly across org.
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8. an open, sharing culture
Being data-driven means having…
No data hoarding or silos. Bring data together
to create rich contexts. Connect the dots.
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9. a self service culture
Being data-driven means having…
Business units have necessary data access as well as within-
team analytical skills to drive insights, actions, and impact.
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10. a broad data literacy
Being data-driven means having…
All decision-makers have appropriate skills to use and interpret data.
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11. an objective, inquisitive culture
Being data-driven means having…
“Do you have data to back that up?” should be a question that no one
is afraid to ask and everyone is prepared to answer—Julie Arsenault.
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12. a visible, clearly-articulated strategy
Being data-driven means having…
Commonly understood vision. Suite of well-designed, accessible
KPIs. All staff understand how their work ties back to these metrics.
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13. strong data leadership
Being data-driven means having…
A head of data to evangelize data as strategic asset with
budget, team, and influence to drive cultural change.
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14. but bottom up too
Change should not just be top-down
Everyone in org has role and responsibility through “leveling up” their
data skills, mutual mentoring, and embedding data into their processes.
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15. blindly following data.
Being data-driven doesn’t mean
Augment decision makers with objective, trustworthy, and relevant data.
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16. using data to effect impact and results
Ultimately, data-driven means
Push data through “analytics value chain” from collection, analysis,
decisions, action, and finally to impact. Partway along chain doesn’t count.
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17. Want to find out more?
There’s lots more detail and practical information in the book including
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• how to design metrics
• how to prioritize data source collection
• best practices of A/B testing
and broader topics such as
• decision making
• organizational structure
• privacy, ethics, and risk