Summary
This session is focused on developing an understanding of how knowledge repositories can lead to deep insights in businesses large and small. It will explore the problem space and present strategies for overcoming those problems. Some example problems knowledge repositories can solve are: missing out on valuable information that can be useful across the company due to silos; repeating research that has been conducted already and inconsistency in research reporting.
Key Insights
-
•
Longitudinal research like diary studies reveals how user experience evolves over time with a product.
-
•
Knowledge repositories enable connecting research findings across different methodologies for richer insights.
-
•
Bridging seemingly unrelated domains, like insurance quoting and buying plane tickets, uncovers valuable user experience parallels.
-
•
Sharing research findings across company silos promotes empathy, innovation, and reduces duplicated effort.
-
•
A multi-level taxonomy system with label, tag, and property-value layers is essential for organizing and retrieving nuanced insights.
-
•
Consistent report structures across different research types facilitate easier consumption and cross-study comparison.
-
•
Knowledge repositories accelerate employee onboarding by allowing deep exploration of products, personas, and features.
-
•
Serendipity in innovation can be enabled by exploring relationships uncovered in well-structured knowledge repositories.
-
•
Research ops roles are critical for maintaining taxonomy governance and keeping knowledge repositories relevant and usable.
-
•
Pilot success factors include ease of data ingestion, search/filter functionality, and clarity of report delivery to stakeholders.
Notable Quotes
"You can capture deep insights by looking at how users’ experiences change as they become familiar with a tool over time."
"Knowledge repositories help you connect different research findings across studies, products, and even different companies."
"Bridging those silos within a company is really important because there’s so much wisdom locked in different groups."
"A taxonomy system is basically a way to tag different findings and reports so you can find relationships later."
"Tags shouldn’t change very often; there should be governance to keep things consistent and relevant."
"Stakeholders can do their own searching at a high-level label level, while researchers dive deeper into nuanced tags."
"We found a lot of points of confusion where tools don’t really align, causing frustration for end users."
"Having leadership involved early with demos and feedback helps smooth the path to adopting a knowledge repository tool."
"Research ops is definitely a role that handles managing the knowledge repository and taxonomy governance."
"Serendipity happens when you explore across different journeys, personas, and contexts in the knowledge repository."
Or choose a question:
More Videos
"Shamus Bern will talk about how to drop into a client site and grok what’s going on quickly without sacrificing why they hired you."
Dan WillisTheme 3: Intro
January 8, 2024
"Small incremental changes are better than no changes at all from both the process and technical view."
Alexis LucioScaling Accessibility Through Design Systems
June 9, 2022
"Consistency is so important that sometimes even consistency in failure works if it means I only have to learn the workaround once."
Sam ProulxOnline Shopping: Designing an Accessible Experience
June 7, 2023
"Combining the what we see in data with the why we get from user research is where true insights live."
Andrew MichaelBuilding a Product Insights Team
March 10, 2022
"The pandemic flipped the equation, and IBM became the place that design talent left."
Dante GuintuHow to Crush the Talent Crunch
September 8, 2022
"Building a great culture means caring for individuals and creating rituals like recognition and shared learning."
Liam ThurstonWhy Your Design Team Is Quitting, And How To Fix It
June 10, 2022
"When I was at IBM, embedded designers were expected to fit in seamlessly, which was an honor."
Smitha Papolu Nova Wehman-Brown Melissa Schmidt Adam MenterTheme 3 Discussion
January 8, 2024
"Bad data in, bad data out — making sure research participants are diverse by race, gender, tenure, and location is crucial for inclusive products."
Anna Avrekh Amy Jiménez Márquez Morgan C. Ramsey Catarina TsangDiversity In and For Design: Building Conscious Diversity in Design and Research
June 9, 2021
"AI is very biased. We have a lot of work to do to get the bias out before going further with many systems."
Erin MaloneUnderstanding the past to prepare for the future
July 19, 2024