Data Analytics: Data analytics encompasses a broad range of activities that IDinsight go beyond the data analysis typically conducted as part of an evaluation. These include, but are not limited to:
Modeling: Building models to allow clients to compare different scenarios; for example, to explore the relationship between key assumptions, inputs and programmatic costs, and/or outcomes. In some cases, a dynamic model (e.g. Excel workbook) is provided as a deliverable so that the client can update the model with their own data or assumptions.
Analysis: Using existing data (which may or may not be collected by IDinsight) to explore operational and contextual questions about a program and/or quickly test initial hypotheses about a program’s impact.
Visualization: Using visual techniques to represent, analyze, and allow clients to interact with data, with the ultimate goal of informing decisions. This can include designing dashboards or mapping.
Living Goods: IDinsight worked with Living Goods in a short-term engagement to develop an impact measurement strategy for its line of nutrition products. During this engagement, IDinsight created a quantitative spreadsheet model that Living Goods could use as it scaled up to estimate its impact across different geographies and further investigate measurement gaps. IDinsight also provided recommendations for specific monitoring and evaluation activities Living Goods might incorporate into its four-year strategic plan based on insights from the theory of change and model.