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Effective Data Management in Evaluation of Innovation & Entrepreneurship by Stefanie Leite and Olivia Noel

Hello! We are Stefanie Leite and Olivia Noel, internal evaluators on the Data Intelligence team at VentureWell. VentureWell is a national nonprofit headquartered in Hadley, Massachusetts, that specializes in funding, training, and cultivating a pipeline of science and technology inventors, innovators, and entrepreneurs. Together with our partners, we are driven to solve the world’s biggest challenges and create positive social and environmental impact.

Innovation and data-driven decision making are at the core of everything we do. This includes our approach to developing scalable systems for data management to support innovation and entrepreneurship (I&E) programs that vary by strategy, program activities, and output and outcomes measures. In this blog, we will share with you a few lessons we’ve learned about innovative approaches to data management within the nonprofit I&E space.

Building for Scale, Allowing for Flexibility

Building data management systems for scale allows us to produce insights at the program-, vertical-, and organizational levels which is important for reporting our impact while supporting ongoing organizational learning. At the same time, the data management needs of individual programs can vary. We use a centralized system for storing data in a structure that supports all that is consistent and stable across programs. We design smaller systems to support data that is unique to programs and we design them specifically for the workflow needs of program staff while ensuring that records are tidy and can be matched with those in other systems. 

Rad Resource

Designing for workflow is an important consideration for use, because even the most elegantly organized system will go unused if it is onerous for users to maintain. One of the tools we use to design systems by workflow is Airtable. In Airtable, you can quickly set up a data collection form that is connected to a table within the base for data entry. You can design interfaces for your users that enable them to interact with their data, such as search, add or modify records, display, filter and summarize data on a dashboard. You can create specialized fields that “roll up” or perform a calculation, and configure automations that perform useful actions, such as creating records, modifying data, or sending emails. Designs that perform tasks for users and calculate and display metrics reward users for their good data stewardship while enabling performance monitoring in live time. 

We continuously learn from how our users interact with the base and we iterate based on their feedback along the way. We apply best practices to new bases we create, too. We document the data structure, fields and processes used for maintenance in a way that enables new users and administrators to learn the system quickly. In this way, data management systems become a multi-faceted learning tool that supports the delivery of high quality, data-informed programs and services.

Please check out our post tomorrow on using extant data to increase DEI in I&E!


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