Data-Driven Decision Making Framework

Design a data-driven decision making (DDDM) framework for [Company]. Include: 1) Decision taxonomy — categorize decisions by reversibility (one-way door vs two-way door), impact (strategic, tactical, operational), and data availability. Different rigor for each category. 2) Decision framework — for each category: who decides (RACI), what data is required, acceptable evidence levels, time allocation, documentation requirements. 3) Data requirements matrix — for strategic decisions: what data to gather, analysis methodology, confidence thresholds, when gut feeling is acceptable. 4) Meeting protocols — data presentation standards (always lead with data, then interpretation, then recommendation), pre-read requirements, decision documentation template. 5) Dashboard culture — executive dashboard design (10 key metrics), department dashboards, metric review rituals, anomaly investigation process. 6) Experimentation mindset — hypothesis-driven approach to business decisions, pilot program design, success criteria before launching initiatives. 7) Common cognitive biases — anchoring, confirmation bias, survivorship bias, sunk cost fallacy. Recognition techniques and mitigation strategies for each. 8) Data literacy program — basic statistics training for all managers, data interpretation workshops, common misinterpretation patterns. 9) Tools and infrastructure — self-serve analytics access, dashboard tools, decision log template, retrospective process for past decisions.