Data Analytics: Foundations to Practice · Foundations of Data Analytics
Data-Driven vs Data-Informed Decision Making
These two phrases sound similar but describe genuinely different relationships between data and judgment, and conflating them leads to two different, equally real failure modes. This chapter draws the distinction.
A purely data-driven approach treats data as the final, sole arbiter of a decision: if the numbers say one option outperforms another, that option is chosen, full stop, with minimal room for other considerations like context, ethics, brand identity, or the practical constraints a purely numerical view might not fully capture.
Key Takeaways
- A purely data-driven approach treats data as the final, sole arbiter, with minimal room for context, ethics, or practical constraints.
- A data-informed approach uses data as one important weighted input alongside domain expertise and organizational context.
- Purely data-driven thinking breaks down when data is incomplete, biased, or measures a proxy rather than what genuinely matters.
- Most mature organizations land on data-informed decision making, combining data and judgment rather than letting either one override the other by default.