This standard ensures that confidence levels in data are clearly visible and well-understood at the point of decision-making. It enables teams to make faster, safer, and more informed choices by surfacing data reliability alongside the data itself.
Aligned to our "Data-Driven Decision-Making" policy, this standard strengthens trust in systems, reduces rework caused by poor-quality data, and supports a more transparent, accountable engineering culture.
Level 1 – Initial: Data is used in decision-making without clear indication of its quality or reliability. Confidence levels are assumed or ignored.
Level 2 – Managed: Some teams annotate data with basic quality indicators, but practices are inconsistent and often manual. Confidence is discussed but not formalised.
Level 3 – Defined: Confidence levels are consistently defined, documented, and presented alongside data. Teams are trained to interpret and act on data reliability during decision-making.
Level 4 – Quantitatively Managed: Data confidence is measured using defined criteria (e.g., freshness, completeness, accuracy). Dashboards and decision-support tools display confidence levels clearly at the point of use.
Level 5 – Optimising: Confidence insights influence data architecture, pipeline prioritisation, and governance. Teams continuously refine how data quality is surfaced and factored into strategic and operational decisions.