Data-Driven Decision-Making

Most workplace decisions fail before the first number is gathered — not because the decider could not think, but because nobody taught them what evidence is for. The question gets framed after the answer is already favored, a metric gets quoted without anyone asking what it counts, an average gets trusted while the spread underneath it carries the whole story, and a chart gets believed because it looks clean. This course teaches deciding with evidence. You will learn to frame the decision before the data, to state in advance what evidence would change your mind, to choose what to measure and to interrogate what a metric actually counts, to keep denominators and base rates in view, to read averages alongside distributions, to compare like against like, and to distrust — politely, precisely, and on evidence — the chart that is trying to sell you something. You will learn to count both sides of a trade-off, to decide honestly inside a range of uncertainty, to update when the data changes instead of defending the first answer, and to present a recommendation that carries its claim, its evidence, and its limits in the open. The course works on your actual decisions throughout: bring real decisions, anonymized, and leave with them framed, checked, and defensible.