Value Engineering: How to Get Your Big Data Investment.....
summary
Argues that enterprises fund analytics only after near-term returns are proven, citing trillions lost to bad data, 40% of the Fortune 100 claiming data-driven success, and McKinsey’s 16% of digital transformations improving performance. Uses a stairway to value approach: build a shared KPI, curate only the data needed, run a small proof that generates incremental revenue (examples: donor resegmentation uncovering thousands of higher-value donors; amusement-park ride downtime reduction), then scale with governance and lightweight production integration.
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chapters (12)
- 0:00Introduction
- 2:17Data and Analytics
- 4:39Two sets of stakeholders
- 7:26The stairway to value
- 9:15Value engineering
- 11:30Stakeholder management
- 14:15Digital envisioning process
- 16:04Value engineering process
- 17:10Value engineering example
- 20:57Whats next
- 24:50Digital Innovation Governance
- 26:43Recap
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