The Science Analytics Never Shipped

• The gap that is not ignorance — why one 1984 result became every BI default and the rest stayed in the literature
• The capacity that does not scale — working memory, cognitive load, and the arithmetic of forty findings
• The obvious fix, and what the data did to it — what explanations actually buy
• What works, and what it costs — cognitive forcing and the satisfaction trade-off
• The variable underneath — verification cost, and how to make it a number
• Where attention goes — surprise, bad news, the information gap
• The single-format assumption — the hospital dashboard we would no longer defend
• The cost of telling a story — narrative transportation and the reader’s guard
• The management implication — four questions that rarely appear on a procurement checklist
• A note on method — where AI was used, and what three verification passes found

“Some of what we have been calling a culture problem is a design problem wearing a culture problem’s clothes.”

— from Why I wrote this

Ali Yıldırım — Founder and CEO, D-CAT Group. Twenty-five years in enterprise business intelligence. Computer Engineering, Boğaziçi University; MBA, Istanbul Bilgi University.

Ten sections, twenty sources, one argument: the defaults were set before most of the research arrived. Each source is listed with what it actually found — including the ones that cut against the argument here.