Deconstructing the automatable decision

Organizations frequently fail at automation projects because they conflate data availability with actual data-driven decision-making, leading to expensive failures when automating processes that require hidden human judgment or rely on inaccurate data. CIOs must distinguish between three categories of decisions—truly data-driven, data-informed, and data-ignored—and invest upfront in discovery work to map how decisions are actually made before automation, as skipping this step can cost 10x the original budget with systems nobody trusts. The real ROI opportunity lies in automating only the highest-value, truly data-driven decisions while recognizing that most operational decisions require human oversight and judgment that cannot be easily replicated by automation.