
A Blueprint For Your Nonprofit Data
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このコンテンツについて
- Taking a holistic approach to data is essential for nonprofits to measure impact and make informed decisions.
- Building comfort and confidence with data requires a combination of technical capacities and a data culture.
- Prioritizing and making incremental improvements in data collection and processes can lead to significant progress.
- Defining terms and asking the right questions are crucial for effective data measurement and analysis.
Bios
Erin MacKenny has a background in education and close to 10 years of experience working in poverty reduction in the non-profit sector. Throughout her career she has developed a passion for evaluation as a means to understand impact. Currently she is the Program Director and Measurement, Evaluation and Learning Lead at the Saint John Learning Exchange in Saint John, NB Canada. In her role she leads the charge in developing stronger and more efficient data collection processes, creating and incorporating new tools, building the organization's data culture, and getting the team excited about the impact of their work. She loves to make talking about data fun and has been known to throw a great data party!
Alberta Johnson is the Manager of Data Solutions and Strategy at Blueprint. She leads a team of amazing humans that work on both the Practitioner Data Initiative and Blueprint's Data Solutions team.The Practitioner Data Initiative is a portfolio of projects funded by the Future Skills Centre, that seeks to develop a set of tool to improve data capacity in the non-profit sector. This includes managing a team to work directly with non-profits and engaging in a set of strategic sector-wide research activities. Blueprint's Data Solutions team implements, manages, and integrates Salesforce to support Blueprint's various research activities. Using agile methodologies, we work with every research team across the organization to support the distribution of surveys and incentives, the tracking of administrative data for programs, reporting at the project/program level, and data security and management practices to ensure the protection of participant's research data.
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