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Engage Your Stakeholders with Data Parties

This interactive webinar will cover the who, what, why, when, and how of hosting a data party. Using engaging lecture, demonstrations, real-life examples, and chat box discussion, presenter Kylie Hutchinson will share practical tips and techniques for data parties including format options, potential pitfalls, and ways to engage stakeholders in making better sense of evaluation and research data. 

26th February, 2019
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About data parties

You've been tasked with doing an evaluation, research project, or collecting data for your nonprofit program, and have analysed the data. Your next task is to write a final report...or is it? What about hosting a data party?

Data parties are a participatory session where you sit down with your stakeholders to collaboratively explore and interpret the initial results. Data parties are an important but often underutilized activity for promoting the uptake of recommendations, knowledge translation and a learning culture. 

Learning Objectives

Upon completion of the webinar participants will be able to:

  • List reasons for holding a data party.
  • Identify different options for hosting. 
  • Explain various activities to help stakeholders engage with your data and results.  
  • State three tips for overall success.


Kylie Hutchinson is an independent evaluator and Principal of Community Solutions Planning & Evaluation. Kylie's passion is developing practical and timely resources for evaluators and nonprofits. She is the author of three books on evaluation and program planning: A Short Primer on Innovative Evaluation Reporting, Evaluation Failures: 22 Tales of Mistakes Made and Lessons Learned, and Survive and Thrive: Three Steps to Securing Your Program's Sustainability

Target Audience

This session will appeal to emerging and seasoned evaluators and researchers new to the practice of data parties, as well as nonprofit staff tasked with evaluating their programs and services.

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Event Suggested By
Principal, Community Solutions Planning & Evaluation.