Redefining data science skill, biased policy decisions, and data strategy.
Analytics translators wanted, algorithm vs. human, and winning with diversity.
1. Biased analysis → Misunderstood cause-effect In Biased Ways We Look at Poverty, Adam Ozimek reviews new evidence suggesting that food deserts aren’t the problem, behavior is. His Modeled Behavior (Forbes) piece asks why the food desert theory got so much play, claiming “I would argue it reflects liberal bias when it comes to understanding […]
Meetup 25-Jan-2018: Papers We Love
1. Hire analytics translators → Keep data scientists happy An emerging role – what some call the Analytics Translator – is offloading burden from data scientists, while helping business executives get better value from their technology investments. A recent HBR piece explains You Don’t Have to Be a Data Scientist to Fill This Must-Have Analytics […]
Valuing patient perspective, moneyball for tenure, visualizing education impacts.
Our founder, Tracy Allison Altman, will talk about behavioral economics for software design @ Papers We Love – Denver on Jan 25. Tversky and Kahneman’s classic “Judgment under Uncertainty: Heuristics and Biases” challenged conventional thinking about bias in decision making, inspiring new approaches to cognitive science, choice architecture, public policy, and the underlying technology. Join […]
Building trust with evidence-based insights.
1. Formalized decision process → Conflict about criteria It’s usually a good idea to establish a methodology for making repeatable, complex decisions. But inevitably you’ll have to allow wiggle room for the unquantifiable or the unexpected; leaving this gray area exposes you to criticism that it’s not a rigorous methodology after all. Other sources of […]
Improving vs. proving, plus bad evidence reporting.
This week we examine how executives can more fully grasp complex evidence/analysis affecting their outcomes – and how analytics professionals can better communicate these findings to executives. Better performance and more trust are the payoffs. 1. Show how A → B. Our new guide to Promoting Evidence-Based Insights explains how to engage stakeholders with a […]
Free beer! and the “Science of X”.
If you view gathering evidence as simply a means of demonstrating outcomes, you’re missing a trick. It’s most valuable when part of a journey of iterative improvement. - Frances Flaxington 1. Immigrants to US don't disrupt employment. There is little evidence that immigration significantly affects overall employment of native-born US workers. This according to an expert panel's […]
$15 minimum wage, evidence-based HR, and manmade earthquakes.
1. Free beer for a year for anyone who can work perfume, velvety voice, and 'Q1 revenue goals were met' into an appropriate C-Suite presentation. Prezi is a very nice tool enabling you to structure a visual story, without forcing a linear, slide-by-slide presentation format. The best part is you can center an entire talk […]
Rapid is the new black, how to ask for money, and should research articles be free?
Photo by Fightfor15.org 1. SPOTLIGHT: Will $15 wages destroy California jobs? California is moving toward a $15/hour minimum wage (slowly, stepping up through 2023). Will employers be forced to eliminate jobs under the added financial pressure? As with all things economic, it depends who you ask. Lots of numbers have been thrown around during the […]
Inspire people with insights, Part 2.
1. #rapidisthenewblack The need for speed is paramount, so it's crucial that we test ideas and synthesize evidence quickly without losing necessary rigor. Examples of people working hard to get it right: The Digital Health Breakthrough Network is a very cool idea, supported by an A-list team. They (@AskDHBN) seek New York City-based startups who […]
To be inspired, your audience needs to see how findings are reliable and relevant. Part 1 talked about creating practical checklists to ensure data-driven research is reproducible. This post describes how to deliver results that resonate with your audience. It’s nice when people review analytical findings, think "Hmmm, interesting," and add the link to bitly. […]