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What UX research maturity looks like and how we get there [Advancing Research Community Workshop Series] (Videoconference)
Thursday, November 9, 2023 • Advancing Research Community
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What UX research maturity looks like and how we get there [Advancing Research Community Workshop Series] (Videoconference)
Speakers: Megan Blocker , Lada Gorlenko , Fatimah Richmond and Molly Stevens
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Summary

Three of your research colleagues discussed and defended their respective positions on what UX research “maturity” looks like. Participants then engaged with them in a discussion and Q&A, facilitated by Lada Gorlenko.   “Absent a strong baseline level of data fluency, product teams struggle to harness the power of insight in their work. As UX and UXR leaders, we are uniquely positioned to define what fluency looks like for our organizations and help teams transform to achieve it.”   – Megan Blocker “Research has come a long way, but we have a long way to go. Our future success rests on two pivotal aspects of maturity: our leadership’s proximity to power and the use of ‘Strategic Research Programs’ to deliver value beyond Design and Product.“  – Fatimah Richmond “Does UX maturity matter in the age of Generative AI? Is your ability to do well as a team going to depend on your UX skills? Or your tech or people skills?”  – Molly Stevens

Key Insights

  • Research maturity involves both knowing what to do and what not to do, requiring responsibility and judgment.

  • Maturity should be seen as a growth mindset, acknowledging continuous learning rather than a fixed state.

  • Elevating research operations from process facilitators to strategic leaders is crucial for advancing organizational maturity.

  • Organizational culture and team data fluency are key to successful research maturity, not just researcher capabilities.

  • Assessment of research maturity works best as a collaborative team activity rather than individual critique.

  • Impact metrics should include the scale and quality of decisions influenced, not only the quantity of completed projects.

  • AI can increase efficiency in data synthesis and administration but should not replace human-led interpretation and team alignment.

  • It’s essential to measure where AI improves research, clarifying what parts of the research lifecycle are affected to reallocate human effort.

  • Embedding research leadership closer to strategic units like strategy or market research can increase influence and maturity.

  • Future research roles may evolve beyond UX/design labels into broader, insight-driven organizational functions.

Notable Quotes

"Maturity is when I know what I do, I'm confident in what I do and I know how to do it."

"Research maturity to me comes down to that growth mindset that there is always more to learn."

"We need to examine power dynamics and leadership practices to truly advocate for UX research."

"Research operations should own delivering impactful data and metrics at the leadership table."

"Teams should self-assess their data fluency in collaborative ways, focusing on strengths and growth areas."

"We should measure not just the output of research but who championed it and what decisions it influenced."

"AI tools can speed up synthesis but relying on them entirely means missing the team's alignment and empathy building."

"It's a moral obligation that organizations engage with research and ethics, not an optional add-on."

"Research can become an embedded capability across all business units, not just part of product or design."

"The velocity of research will speed up with AI, but interpretation and recommendations remain human responsibilities."

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