1/2 Qualitative & quantitative data: #QuantData measures how much, and #QualData represents conceptual patterns. Both have an "iffy" version full of assumptions and a solid, reliable version, two ends of the spectrum for both types of data. (For qual, reliable patterns occur at data saturation.)

1/2 💡Why is empirical research important, in dollars & cents?💰
Both #QuantData as for #QualData have subjective vs empirical outcomes. The subjective end of the spectrum is risky. It’s not representative, or only spottily represents tiny segments, or it misrepresents entirely.

1/3 If your org is "data driven," most likely the majority of that #data is #QuantData about how people are interacting with your solutions. This misses the human cognitive & emotional side of the equation. We need to humanize this. Rebalance it.

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