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Delivering Excellence in the Age of AI or Association 4.0

.orgSource

Understand the Imperative To keep pace with member expectations, acknowledging that disruption and change are business as usual is critical. Self-evaluation isn’t easy. The willingness to scrutinize performance on an ongoing basis begins with the board and the management team.

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Study the Data, But Eat the Cake—Put the Human Factor Forward

.orgSource

Machine Learning, predictive modeling, and natural language processing are a few of the ways AI makes data more meaningful. Predictive modeling reveals future outcomes and trends with greater accuracy than traditional methods, enabling proactive decision-making and change management. It’s free with limited usage.

Data 221
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The Unrecognized Risk of Status Quo Problem-Solving Skills for Grantmakers

sgEngage

Nonprofits show and share what worked, usually with tidy stories and charts. They know they can’t really share everything that happens behind the curtain (and believe me, there is so much that never reaches beyond the walls of most organizations) because they will risk the loss of funding.

Problem 84
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Beyond the Newest Philanthropy Buzzword: Knowledge Work Is Core to Equitable Change

sgEngage

Sadly, many current change efforts that try to incorporate knowledge work for social good end up with disjointed or burdensome lists of isolated activities that really aren’t very engaging or valuable. As we reaffirm shared meaning making, we realize that knowledge work and social change are quite intertwined and interdependent.

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Is the Higher Education Pipeline Shrinking or Just Taking a Nap?

sgEngage

Colleges and universities that historically relied on their reputations may have to adapt their models to attract and retain different student populations, such as adult learners, online students, or individuals seeking tangible professional development opportunities. Re-evaluate your messaging. For example, the U.S.

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Navigating Nonprofit Data Warehouses: A Comprehensive Guide

DNL OmniMedia

Segmentation is the process of grouping your supporters based on shared characteristics. This might involve establishing data models and structures that allow you to standardize information from a variety of sources, validating that information, appending your data with additional details, and prioritizing data security.

Data 52
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How do you create a culture that is not afraid to fail (or be more receptive to social media?)

Beth's Blog: How Nonprofits Can Use Social Media

A few weeks ago, I had the pleasure of hearing Michael Quinn Patton , an evaluation guru, speak at the Packard Foundation. He described the challenges of adapting evaluation methods to non-Western systems in developing countries because evaluation has traditionally been deeply rooted in the Western ways of thinking.