The Analytics Power Hour #291: The Data Work that Lives in the Shadows
24 snips
Feb 17, 2026 They unpack the unseen "shadow work" analysts do to make data usable, from admin and project follow-up to rebuilding warehouses. They talk alignment challenges like standardizing metrics, explaining data realities, and teaching non-analysts. They cover risks of tribal knowledge, monitoring expectations, and how to make this hidden work visible and hire to fill gaps.
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Fix Architecture Before Trusting AI
- Don't assume AI fixes poor data architecture; fix structure and provenance first.
- Invest in standardization and architecture before layering ML or generative tools.
Complexity Creates Single-Point Bottlenecks
- When complexity concentrates in one or two people, you create bottlenecks and single points of failure.
- Flexibility without standardization leads to knowledge silos and operational risk.
Assign Shadow Work Strategically
- Map tasks to people's strengths and redistribute shadow work intentionally across the team.
- Hire complements for gaps like documentation, program management, or stakeholder education.
