Tracy Allison Altman

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Smart decision-making is more complicated than becoming ‘data-driven’, whatever that means exactly. We know people can make better decisions if they consider relevant evidence, and that process is getting easier. But too often tech enthusiasts dismiss people’s decisions as based on gut feel, as if data will save us from ourselves. Let’s put an end to...
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1. Lori C. Bieda of SAS is spot on, describing how analytics professionals can grow into roles as trusted advisors for senior executives. In The Translation Layer: The Role of Analytic Talent, she explains that “Analytics teams… need to evolve from data providers into insight integrators.” Lots of detailed observations and recommendations in this white...
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calculator saying I don't Know
Sometimes we fool ourselves into thinking that if people just had access to all the relevant data, then the right decision – and better outcomes – would surely follow. Of course we know that’s not the case. A number of things block a clear path from evidence to decision to outcome. Evidence can’t speak for...
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What works reading list
1. Abundant evidence → Clever synthesis → Informed crime-prevention decisions The What Works Crime Toolkit beautifully synthesizes – on a single screen – the evidence on crime-prevention techniques. This project by the UK’s @CollegeofPolice provides quick answers to what works (the car breathalyzer) and what doesn’t (the infamous “Scared Straight” programs). Includes easy-to-use filters for...
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prison inmate in orange clothing
1. Jason Zweig tells the story of randomistas, who use randomized, controlled trials to pinpoint what helps people become self-sufficient around the globe. The Anti-Poverty Experiment describes several successful, data-driven programs, ranging from financial counseling to grants of livestock. 2. Can an early childhood program prevent child abuse, crime, drug abuse, and neglect? Yes, says...
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1. CircleUp uses algorithm to evaluate consumer startups. Recently we wrote about #fintech startups who are challenging traditional consumer lending models. CircleUp is doing something similar to connect investors with non-tech consumer startups (food, cosmetics, recreation). It’s not yet a robo adviser for automated investing, but they do use machine learning to remove drudgery from...
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“What counts as good evidence?” is a great conversation starter. The UK-based Alliance for Useful Evidence / Nesta offers seminars and publications to “explore what is realistic in terms of standards of evidence for social policy, programmes and practice.” Prompting discussion was a ‘provocation paper’, What Counts as Good Evidence?, by Sandra Nutley, Alison Powell,...
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1. Evidence standards → Knowing what works → Pay for success Susan Urahn says we’ve reached a Tipping Point on Evidence-Based Policymaking. She explains in @Governing that 24 US governments have directed $152M to programs with an estimated $521M ROI: “an innovative and rigorous approach to policymaking: Create an inventory of currently funded programs; review...
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patient value
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...
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1. SPOTLIGHT: MCDA, a decision process for everyone. ‘Multiple criteria decision analysis’ is a crummy name for a great concept (aren’t all big decisions analyzed using multiple criteria?). MCDA means assessing alternatives while simultaneously considering several objectives. It’s a useful way to look at difficult choices in healthcare, oil production, or real estate. But oftentimes,...
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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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