When working with organizations, we often see leaders with good intentions make a simple mistake: taking their data at face value instead of looking deeper into the numbers. But when you take your data at face value, this can often lead to incorrect and counterproductive conclusions. Consider an organization seeking to improve the graduation [...]
Data can often be the missing link in a collective impact initiative. However, data plays a substantial role in informing the collective. It has a significant role in the initial planning and determination of focus for collective initiatives, enabling the approach to be greater than simply collaboration. An area that many collectives find challenging is [...]
Frank Farrow, Director of the Center for the Study of Social Policy, discusses the importance of data informed decision making. The combination of rich, detailed and comprehensive data with a larger understanding of community and program needs is data informed decision making at its best. Good decision making has its roots in data and can [...]
The Short Answer 1. Start by assessing the result in terms of everyday experience, what we see hear, or feel about children ready for school or stable families. 2. Brainstorm a list of candidate indicators. Each entry is a data statement, e.g. % of children reading at grade level, rate of foster children per 100,000. [...]
The Short Answer 1. Look at what others have done. There are many websites with report cards and data sources that others have used. (See tools.) 2. Get your partners to help access what now is produced. Sometimes the best data on child and family well-being comes from the public health and education systems. State [...]
The Short Answer 1. Use the results and the experiential version of results to drive the process. Instead of asking "How are we doing on the baseline?" we ask "How are we doing producing the result we want?" How prevalent are the experiences which tell us about this result?" "Are things getting better or worse? [...]
The Short Answer 1. Identify the measures for which you currently have data. 2. Choose the most important using a forced choice process, asking: "If you had to talk about your program with just one of these circled measures, which one would it be?" 3. Identify your data development agenda using a forced choice [...]
The Short Answer 1. Start with the data you already have. Most programs collect far more data than they use. Do not start the process by collecting new data. 2. Create new data where necessary. Be creative. Use common sense sampling techniques. Some data is better than no data. Full Answer Existing sources and [...]
