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Because Data Can't Speak for Itself

A Practical Guide to Telling Persuasive Policy Stories

David Chrisinger and Lauren Brodsky

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A guide for how to tell clear, data-driven stories that will make an impact.

People with important evidence-based ideas often struggle to translate data into stories their readers can relate to and understand. And if leaders can't communicate well to their audience, they will not be able to make important changes in the world.

Why do some evidence-based ideas thrive while others die? And how do we improve the chances of worthy ideas? In Because Data Can't Speak for Itself, accomplished educators and writers David Chrisinger and Lauren Brodsky tackle these questions head-on. They reveal the…

A guide for how to tell clear, data-driven stories that will make an impact.

People with important evidence-based ideas often struggle to translate data into stories their readers can relate to and understand. And if leaders can't communicate well to their audience, they will not be able to make important changes in the world.

Why do some evidence-based ideas thrive while others die? And how do we improve the chances of worthy ideas? In Because Data Can't Speak for Itself, accomplished educators and writers David Chrisinger and Lauren Brodsky tackle these questions head-on. They reveal the parts and functions of effective data-driven stories and explain myriad ways to turn your data dump into a narrative that can inform, persuade, and inspire action.

Chrisinger and Brodsky show that convincing data-driven stories draw their power from the same three traits, which they call people, purpose, and persistence. Writers need to find the real people behind the numbers and share their stories. At the same time, they need to remember their own purpose and be honest about what data says—and, just as importantly, what it does not.

Compelling and concise, this fast-paced tour of success stories—and several failures—includes examples on topics such as COVID-19, public diplomacy, and criminal justice. Chrisinger and Brodsky's easy-to-apply tool kit will turn anyone into an effective and persuasive evidence-based writer. Aimed at policy analysts, politicians, journalists, teachers, and business leaders, Because Data Can't Speak for Itself will transform the way you communicate ideas.

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Because Data Can't Speak for Itself

David Chrisinger and Lauren Brodsky

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Reviews

Because Data Can't Speak for Itself offers a joyful romp through the craft of policy writing that will inspire students and policy professionals alike to cut through the ubiquitous noise of the information age and infuse data with meaning, clarity, authenticity, and purpose—so we might see the forest for the trees through the power of story.

I glimpsed into the crystal ball and saw policy reports unafraid of complexity and contradiction; analytical writing that champions persistence, patience and honesty; texts tackling the tricky connection between data and interpretation with dexterity. How did we get to that much-needed future of better data-driven policy writing? With Chrisinger and Brodsky as our travel companions.

In Because Data Can't Speak for Itself, Chrisinger and Brodsky make a compelling case for human-centered and impact-oriented stories using data; and they offer a hugely important lesson for anyone working in policy and social change—to lead with accuracy, honesty, empathy, and humility in using data to inform and persuade.

Many argue that data is the world's most valuable resource. They're wrong, and this book shows why the true value lies in the data refiners, who both learn from data and write a compelling narrative about those data. Bravo to David and Lauren: your stories captivated me from beginning to end, turning the hours to minutes.

About

Book Details

Release Date
Publication Date
Status
Preorder
Trim Size
5.5
x
8.5
Pages
152
ISBN
9781421445847
Illustration Description
3 line drawings
Table of Contents

Contents
Foreword by Ethan Bueno de Mesquita
Introduction
Why Should You Learn to Tell Stories with Data?
Part I: People
Telling Stories with Data about People for People
Part II: Purpose, Then Process
Findi

Contents
Foreword by Ethan Bueno de Mesquita
Introduction
Why Should You Learn to Tell Stories with Data?
Part I: People
Telling Stories with Data about People for People
Part II: Purpose, Then Process
Finding Meaning in the Data and Making It Work for You
Part III: Persistence
Using Data to Solve Wicked Problems with Integrity
Conclusion
Acknowledgments
Tips to Help You Write More Effectively with Data
Notes
Index

Author Bios
David Chrisinger
Featured Contributor

David Chrisinger

David Chrisinger (CHICAGO, IL) is the director of the policy writing program at the University of Chicago’s Harris School of Public Policy. He is the author of Public Policy Writing That Matters and Stories Are What Save Us: A Survivor's Guide to Writing about Trauma and the editor of See Me for Who I Am: Student Veterans' Stories of War and Coming Home.
Featured Contributor

Lauren Brodsky, PhD

Lauren Brodsky (LEXINGTON, MA) is a lecturer in public policy at the Harvard Kennedy School. She teaches courses on policy analysis and persuasive communication and has published articles in Harvard Business Review and Fast Company.