The Influence of Data
The Influence of Data
Data that influences stakeholders
Your stakeholders, your VPs, managers, product owners, etc., are people who have philosophies about how to bring value to the org and how to bring value to the people the org serves. More often than not, our human-focused philosophies align. Our need for substantive understanding of people aligns.
Friction happens when worry about timing arises. “Time equals money” is the saying. “Just give me some quick insights that we can act on now” is the ask.
Yes, we can push back against the ask. We all agree about getting actionable insights, and we agree those insights should not be biased. Quick insights tend to be influenced by the org researcher, and solution context. Assumptions based on quick insights lead to non-strategic or reactive improvements to the solution your org provides to people.
We are all tired of non-strategic or reactive improvements to the solution, stakeholders included.
Here’s a little secret: the “quick” part of finding insights doesn’t come from the time researchers spend with people in listening sessions or interviews. The “quick” part tends to happen in the data analysis.
Qualitative data analysis gets messy and convoluted. It’s hard. Different researchers can see different themes, and discussion takes up time. Common affinity techniques depend upon deterministic categories like steps in a process (and trying to find homes for the concepts that don’t exactly fit). Researchers try to provide meaning within their insights, when meaning is supposed to come later, when insights are compared to solutions or strategies. It’s really hard. We wonder, “How can researchers avoid influencing the data?” How can we represent the ethics and cognition of people in its true variety? Stakeholders are interested in this, too. When you mention it, they will agree.
Getting the value we need from data is crucial, but when it comes to data analysis, it’s difficult to know the exact steps to produce empirical, representative data—especially when “time is money.”
Clear, straightforward steps do exist for bias-resistant data analysis. My two part course on Qualitative Data Synthesis allows any researcher (or conscripted researcher) to produce bias-resistant patterns from a set of transcripts.
Part 1 is how to craft puzzle pieces representing every interior cognition concept from the person’s point of view, written with words that people used to describe their interior cognition.
Part 2 shows how to use the affinity technique of the person’s Focus of Mental Attention, bypassing the researcher’s own perspective. This technique avoids the themes and categories from the org’s field.
The key pivot we want our stakeholders to make is that time also equals stronger understanding of people, more awareness of variety in their approaches, and better value and longevity in the data patterns. And when there are clear steps to follow in data analysis, the value of the outcome is worth the time it takes. The patterns are immediately actionable, and also provide ongoing actions to plan a market strategy around. In the long run, the time invested is tiny compared to the many years that these solid data patterns can be used. When you mention it, stakeholders will be interested.
What people have said about the courses:
“Fills in one important missing piece of the puzzle: how to generate reliably valid qual insights from interviews. I have been looking since I started this career.” Greg Hamilton
“My confidence that my org's qualitative data can be used more strategically over the coming years - not just 1 or 2 sprints - is radically higher. My head is wonderfully exploding with all the ways that I can implement what I've learned into an immature UX environment. Also, the learning is broken into chunks that can be digested before work or at lunch.” Kara Snyder
“Even if you've been a UX research practitioner for a long time, this course will show you how to let data speak for itself and how to group findings without bias.” Augusto Bianchi
“I wish I would have discovered these courses earlier in my career. The care put into the content is evident, and the depth and nuance is unparalleled. I would highly recommend Indi Young's work, and her video training makes concepts she writes about come alive and easier to grasp.” Mo Goltz
Still reading? Yay! Here’s an extra tidbit. I use the phrase “data synthesis” for both parts of the method because it is a bottom-up approach. It allows patterns to emerge from the data, representing the concepts people use to address something their way. “Analysis” sounds so top-down. So I decided not to use that word to represent this method. 😊