Oct 26 2015 Data as a decision-making tool for change

We’re always on the lookout for helpful resources for practitioners and are big fans of Spark Policy Institute’s Tools for Social Innovators, an online resource with practical tools, guides, exercises, and resources meant to enable funders, non-profits, businesses, and community leaders to “enhance their ability to ignite social change.” Spark recently announced a new toolkit, Data as a Tool for Change, which looks at the use of data in decision-making processes within efforts aiming to bring about meaningful change.

“Decision making supported with high-quality data can be more strategic by helping collaborative efforts and individual leaders direct resources to where the greatest impact is possible.”

Data in its many forms is a crucial part of decision making for innovators and change agents. For example, using data to determine future actions can bolster the efficiency and effectiveness of resource allocation. “Decision making supported with high-quality data can be more strategic by helping collaborative efforts … direct resources to where the greatest impact is possible,” according to Spark. At The Intersector Project, we address the role data can play in cross-sector collaboration in two key tactics from our Toolkit: Build a Common Fact Base, which guides partners to establish joint recognition of what data is relevant to the issue at hand, and Commit to Information Sharing, which guides practitioners to develop data sharing methods between stakeholders.

While it’s clear that data is important, Spark’s Data as a Tool for Change toolkit addresses the reality that collection, evaluation, presentation, and use of data can be challenging for practitioners untrained in research methodologies or lacking time for data gathering and analysis. The toolkit provides actionable advice for social innovators across sectors on where to turn for data and how to evaluate and present their results.

Among other topics, Spark’s new toolkit offer practical guidance in:

• Engaging cross-sector partners to answer questions
• Interpreting your data alongside those entrenched in the issues
• Telling the story of your data

Engaging cross-sector partners to answer questions
Look to cross-sector partners for data that will be useful in answering the key questions that will inform your decision-making processes. This practice is a means of “being thoughtful about the data gathering process.” For example, in answering the question “Who is most affected by the problem and why?”, public-sector agencies are likely to have quantitative data identifying the “who” — which population is most affected by the problem being addressed. In this instance, it’s also important to talk with service providers, researchers, and community members, who will have qualitative insights into the “why” part of the question.

Interpreting data alongside those entrenched in the issues
Schedule time, about 30 – 45 minutes, to sit down with key leaders, staff, and partners to explore what the data reveals in relation to the question asked, how the data aligns or conflicts with intuitive and experiential knowledge, and how historical context or anecdotal stories help you understand the data. This is key, as Spark notes, because data only has meaning once it’s interpreted. — It’s useful to have those involved in decision making interpret the collected data because “partners embedded in the problem and its solutions understand what they are seeing,” while an external organization does not.

Telling the story of your data
When presenting data to other stakeholders who  will use the data, tell the story that surfaced during its interpretation. Storytelling is an accessible and actionable way to present the information most relevant to the decision being made. While tables, charts, graphs, maps, and infographics are undoubtedly helpful, accompanying these visual presentations with storytelling “can make your findings relatable thereby making them more actionable,” Spark states.

We recommend Spark’s Data as a Tool for Change to practitioners of multi-stakeholder processes and particularly for intersector collaborations. While the tools are not specifically created for practitioners divided by sector differences, they offer practical advice for identifying relevant data across sectors and applying it to decision making around complex problems and solutions, which often necessitate cross-sector approaches.