4. Work with Your Data to Develop Insights

The steps below will help you walk through the process of analyzing and synthesizing your date whether you collected numeric (quantitative) or text-based (qualitative) data in answering your research questions.

Get familiar. If you are working with text-based data, read and reread the data until it becomes familiar to you.

Compile and organize the data. If helpful, arrange and group the data in a familiar software program so that they are easy to scan and make sense of. If you are accustomed to using Excel, you could compile your data in a spreadsheet.

Perform a quality check. Especially for numeric data, perform a quality check. Look for data entry problems, unusual figures or texts, missing data, etc.

Run the numbers. If you’re working with numeric data, you might want to run calculations, such as:

• Frequencies — Counts of responses, which are useful for indicating how often an event or response occurs.
• Percentages — Share of the total, which indicate how much a response or event occurs in relation to the total data set being examined.
• Averages— Show how typical something is, or…which are useful for….
• Depending on the nature of project and available resources, other, more complicated calculations could be made.

Identify and classify emergent themes. As you spend time with your data, you’ll notice emerging themes and ideas that repeat themselves. Ask yourself: What do the responses have in common? What is surprising about the responses? Look for overlaps and redundancies, which will help you to identify common themes. For your qualitative data, try to create broad categories and smaller subcategories under them. For your quantitative data, look for patterns across the variables, among different groups that you surveyed.

Develop insights. Step back from your data and the themes you have developed. Think about how the ideas and concepts relate with each other. And look to see if an overarching story is revealed. Pick examples from your data that best illustrate the story.

Tools and Examples

Example: Organization of Survey Responses

Example: Number Crunching

Example: Identification of Emergent Survey Themes

Example: Develop Insights from Survey Data