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evidence-based management

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Evidence relativism, innovation as a process, and decision analysis pioneer.

5 September 2016By
1. Panning for gold in the evidence stream. Patrick Lester introduces his new SSIR article by saying “With evidence-based policy, we need to acknowledge that some evidence is more valid than others. Pretending all evidence is equal will only preserve the status quo.” In Defining Evidence Down, the director of the Social Innovation Research Center...
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PepperSlice data-driven presentation

How Warby Parker created a data-driven culture.

4 September 2016By
1. SPOTLIGHT: Warby Parker data scientist on creating data-driven organizations. What does it take to become a data-driven organization? “Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply ingrained data culture,” says Carl Anderson. In his recent O’Reilly book Creating a Data-Driven Organization, he...
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Science of CEO success?, drug valuation kerfuffle, and event attribution science.

18 August 2016By
1. Management research: Alchemy → Chemistry? McKinsey’s Michael Birshan and Thomas Meakin set out to “take a data-driven look” at the strategic moves of newly appointed CEOs, and how those moves influenced company returns. The accompanying podcast (with transcript), CEO transitions: The science of success, says “A lot of the existing literature is quite qualitative,...
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Business coaching, manipulating memory for market research, and female VCs.

27 July 2016By
1. Systematic review: Does business coaching make a difference? In PLOSOne, Grover and Furnham present findings of their systematic review of coaching impacts within organizations. They found glimmers of hope for positive results from coaching, but also spotted numerous holes in research designs and data quality. Over the years, outcome measures have included job satisfaction,...
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Mistakes we make, Evidence Index, and Lebron vs Steph.

8 June 2016By
1. Mistakes we make when sharing insights. We’ve all done this: Hurried to share valuable, new information and neglected to frame it meaningfully, thus slowing the impact and possibly alienating our audience. Michael Shrage describes a perfect example, taken from The Only Rule Is It Has to Work, a fantastic book about analytics innovation. The...
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flower black-eyed susan

Getting to evidence-based policy: Explainista, Randomista, or Mapista?

5 May 2016By
Three Ways of Getting to Evidence-Based Policy. In the Stanford Social Innovation Review, Bernadette Wright (@MeaningflEvdenc) does a nice job of describing three ideologies for gathering evidence to inform policy. Randomista: Views randomized experiments and quasi-experimental research designs as the only reliable evidence for choosing programs. Explainista: Believes useful evidence needs to provide trustworthy data...
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photo of stadium seats

Masters of self-deception, rapid systematic reviews, and Gauss v. Legendre.

24 April 2016By
1. Human fallibility → Debiasing techniques → Better science Don’t miss Regina Nuzzo’s fantastic analysis in Nature: How scientists trick themselves, and how they can stop. @ReginaNuzzo explains why people are masters of self-deception, and how cognitive biases interfere with rigorous findings. Making things worse are a flawed science publishing process and “performance enhancing” statistical...
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Analytics of presentations, Game of Thrones graph theory, and decision quality.

14 April 2016By
1. Edges, dragons, and imps. Network analysis reveals that Tyrion is the true protagonist of Game of Thrones. Fans already knew, but it’s cool that the graph confirms it. This Math Horizons article is a nice introduction to graph theory: edges, betweeness, and other concepts.   2. Teach your team to make high-quality decisions. Few of...
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evidence-based social innovation

‘Evidence-based’ is a thing. It was a very good year.

14 January 2016By
2015 was kind to the ‘evidence-based’ movement. Leaders in important sectors – ranging from healthcare to education policy – are adopting standardized, rigorous methods for data gathering, analytics, and decision making. Evaluation of interventions will never be the same. With so much data available, it’s a non-stop effort to pinpoint which sources possess the validity,...
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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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