‘Effective qualitative analysis answers the Why, not just the What’, reveals Capire Consulting Group’s Koel Wrigley.
In her recent webinar with Bang the Table, Wrigley taps into her extensive work in community engagement projects across Australia and unpacks what to consider when collecting and making sense of subjective responses and feedback – or, qualitative data.
Qualitative data analysis brings community voices and experiences to planners looking to understand how people feel about issues. While this can be hugely valuable it is tricky to unpack, particularly with the open field questions associated with it. But, as Wrigley points out, qualitative analysis can help tell more of the story, answering important questions. Qualitative analysis can take time, she says, and while there isn’t a perfect program to make it simple, there are processes and techniques that can make the job of unpacking subjective data easier.
First, it’s important to consider:
What exactly is qualitative analysis and how is it different from quantitative analysis?
Making sense of information produced by community engagement is vital to understanding how communities feels about the issues at hand. For policymakers, getting an accurate reading of public input or feedback can help inform decisions and move conversations forward. Both qualitative and quantitative analysis have a role in creating this clarity. While quantitative analysis looks at the numbers, qualitative analysis breaks down the subjective information and experiences that come from the engagement.
For instance, surveys can be measured with quantitative analysis to understand how people feel about an issue, and how their responses may be compared by proportion, demographics, or sentiment. When it comes to varied and subjective community reponses around open-ended questions, qualitative analysis picks out the important themes and patterns emerging from these responses, and helps answer the questions that concern policymakers. Qualitative data can be quantified to reveal these themes and patterns for comparison and consideration – and that’s when it becomes a powerful resource for the end user, Wrigley suggests.
What does it mean to have effective qualitative analysis of engagement data?
For Wrigley, effective qualitative analysis is all about answering key questions in ways that go beyond looking at the What to understand the Why.
To this end, being able to quantify qualitative data is crucial to revealing community priorities, the differing themes and issues in community responses, and the underlying demographic factors. Effective qualitative analysis digs deeper to spot and understand these trends and turn conversations with communities into measurable, actionable information for policymakers.
But effective qualitative analysis can’t be tacked on to the evaluation end of the community engagement process. Wrigley highlights the importance of a continuous commitment throughout the process to the questions driving the engagement: from understanding what policymakers want to know from the community, to shaping the questions that move the conversation, to ensuring consistency in how community responses and related vital information are captured and measured.
How does qualitative analysis find meaning in engagement data?
To analyse qualitative data is to turn community conversations into stories which can speak to the questions facing policymakers. The first stage is getting a clear understanding of the questions at the heart of the engagement and the kind of information that the project is expected to produce.
One of Wrigley’s Golden Rules is that the person writing the report should have a role in designing the questions with an eye to their end use. In addition, these questions and the capture of responses must be consistent throughout engagement processes to ensure the integrity of the data. On reading qualitative data, Wrigley underlines the importance of getting an accurate sense of who is saying what. Typically, demographic factors tend to be valuable to the end user, and will have to be captured in the process.
The second stage is in reading and coding these conversations by categories or overarching themes to produce an understanding of how people feel about the issues under discussion, why they do so, and what demographic factors may be of relevance. These broad patterns are identified, organised by theme and presented as readable, measurable information in the ultimate report. Wrigley recommends reading and cross-checking at least a quarter of the data, ensuring that selections represent a variety of the locations or types of stakeholders.
Coding the data, or categorising responses by theme and other factors is crucial to how qualitative analysis breaks down conversations into presentable information. Coding can take an open or inductive approach in looking for emerging themes, or a deductive or selective approach to test preset ideas, or go by question. These findings are then organised and presented to create the story of the engagement and answer its key questions.
Wrigley outlines tips and strategies to keep coding consistent with engagement objectives and make the most of the ways in which tools and techniques can help convey the full picture and the details as necessary. Watch Qualitative Analysis for Community Engagement with Koel Wrigley to learn more about managing, interpreting, and reporting on qualitative data.
Photo by Kelly Sikkema on Unsplash/cc