Creating inclusive data collection practices for program evaluation is more than just a step in the process; it’s about honoring the voices and experiences of those who participate in your programs. By thoughtfully considering the purpose of your data collection, engaging with communities, and offering flexible options,
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We’ve seen a trend in our data collection work lately, and we think it’s time to be candid. For many reasons (including busy schedules, expiring COVID-era funds, stagnant procurement processes, and grant deadlines that sneak up on you), nonprofit and government agencies have boxed themselves in –
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In our first blog post on this topic, we told you, “The cost of a program evaluation will realistically depend on several variables, but a good gauge is to estimate 10-15% of the total program costs.” While this estimate will suffice as an approximation, it should not
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Have you heard about Knowledge Advisory Group’s approach to measurement? It’s a flexible process that we call NIMBLE (Navigate, Include, Magnify, Build, Learn, and Evaluate). NIMBLE works well for nonprofits and other organizations, whether you need to tackle data tasks in small bites or on a larger
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As organizations begin to recognize that data and evaluation are imperative for program development, they are sometimes tempted to look for a quick, silver bullet approach to data collection. In the final blog of our Conquering Data series, we want to caution against the urge to purchase
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In the fourth blog of our Conquering Data series, we’d like to ask you to consider this question: can we truly adopt a mindset of continuous improvement without identifying areas for growth, refinement and action? Over the past decade, Knowledge Advisory Group has encountered many organizations that
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In the third blog of our five-blog series, Conquering Data, we want to share another essential understanding within the funder and nonprofit relationship. After explaining that it is okay to start small and asserting that nonprofits should take ownership of their program outcomes in our first two
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In the second installment of our five-part series, Conquering Data, we’re taking the next step towards doing just that. Last month we focused on dispelling the myth that to make a difference in data and program evaluation you must jump in headfirst. Instead, we asserted that it’s
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It can be overwhelming to think about data and program evaluation. When venturing into this territory it’s only natural to have questions. Where should we begin? What should we measure? How can we find meaning in our data? In the first blog of our five-part series, Conquering
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