1. Understand quantitative people → See what's possible → Succeed with analytics Tom Davenport outlines an excellent list of 5 Essential Principles for Understanding Analytics. He explains in the Harvard Business Review that an essential ingredient for effective data use is managers’ understanding of what is possible. To counter that, it’s really important that they establish a close working relationship with quantitative people.
2. Systematic review → Leverage research → Reduce waste This sounds bad: One study found that published reports of trials cited fewer than 25% of previous similar trials. @PaulGlasziou and @iainchalmersTTi explain on @bmj_latest how systematic reviews can reduce waste in research. Thanks to @CebmOxford.
3. Organizational context → Fit for decision maker → Evidence-based management A British Journal of Management article explores the role of ‘fit’ between the decision-maker and the organizational context in enabling an evidence-based process and develops insights for EBM theory and practice. Evidence-based Management in Practice: Opening up the Decision Process, Decision-maker and Context by April Wright et al. Thanks to @Rob_Briner.
4. Historical data → Statistical model → Prescriptive analytics Prescriptive analytics finally going mainstream for inventories, equipment status, trades. Jose Morey explains on the Experfy blog that the key advance has been the use of statistical models with historical data.
5. Sports data → Study of bias → NFL evidence Are NFL officials biased with their ball placement? Joey Faulkner at Gutterstats got his hands on a spreadsheet containing every NFL play run 2000-2014 (500,000 in all). Thanks to @TreyCausey.
Bonus! In The Scientific Reason Why Bullets Are Bad for Presentations, Leslie Belknap recaps a 2014 study concluding that "Subjects who were exposed to a graphic representation of the strategy paid significantly more attention to, agreed more with, and better recalled the strategy than did subjects who saw a (textually identical) bulleted list version."