Day 3-Positioning Insight: Structuring teams, roles and careers for a changing research landscape

Discussion Panel

Marieke McCloskey: Director of UX Research, LinkedIn

Renee Reid: Director, UX Design Research, LinkedIn

Megan Blocker: Director, Research & Insights, JustWorks

Introduction

1. Start by laying foundation and what we mean by insight and how it’s different from research and how it’s different
   1. MM: For me insight is a-ha moment of new understanding to move something forward and some insights that we UXRs can provide but for most impactful decisions and collective knowledge together
   2. RR: Insight across the board for signals is that insight is what will drive the information to push people and evoke something and inspire people and team and challenge stakeholders as well, and what will light the fire and create change action, and inspiration
      1. The more salient insights are, the more actionable and clear they are, the more people would grab hold
   3. MB: Data and insight I have is that we are doctors, not waiters, and don’t just take orders on what customers or stakeholders say they want, but combine data we uncover and combine it with expertise, context, and organization’s goals and put together insight that spurs to action in right direction or prevents us from moving forward in wrong one
      1. Product of many things
2. Common thread hearing from each of you is that insights are basically ever-reaching and accessible and likely getting to space where we figure out how to address insights not making it over the hill or pushed to the side or misinterpreted it
   1. Silent knowledge has always been a challenge, and how can we see stakeholders blur line between fact and fiction
3. As we look at evolving careers, practices, what are practical strategies to adopt to maintain insight integrity and prevent us from losing credibility?
4. MB: In years past, power was in being generators and bearers of knowledge and think things we can do, and role to come to knowledge and position yourself as coaches and lean into better decisions and being better judges of fact and feeling.
   1. To do it well, need to position self as partner and force of lateral power and leadership to be heard and welcomed and position self as partner and help me to free-up time once good and work on next person and win as well
   2. Whole organization benefits from stance and improving at research and key part for how job should be changing
5. RR: Triangulating insights beyond studies being very important, and take into account what other insights may be happening for org, and have market research and data science
   1. Important to take that into account and build holistic point of view and siloed and pressure test against insights in organization and importance of academia
   2. Take step back to research for secondary research we can leverage, and human behavior — so go into canons of rigor and information to build insights
6. MM: Focus on slowing down and listen to what is coming out of academia. In current function, embedded for business units, and felt crunched in terms of staff and stuck in thought
   1. Took major step back and centralized and way of working for various marketplaces, and letting researchers go deep
   2. Want to take back and work in parallel to product org and product stakeholders
      1. Insights have to scale to whole company and being able to build teams like UX measurement and feel in better place
      2. Work sounds very similar and possible with team of certain size
   3. See whole pictures and are system thinkers looking across the whole thing and see that doing it too

RO: Focus on canonical sources and things that already exist and desk research that isn’t checking the box

4. As knowledge becomes more decentralized and how to balance roles as curators as opposed to creators of insights?

1. MM: Big thing was building out research repository of insights and presented one stage at all hands and offered internal tools
   1. Worked with reops team and vendor to query and provide questions
   2. Mindful that did research and what AI bot can leverage and all transcripts
      1. Hard-coded it to give answers for reference and issues in it and skills where it goes
   3. Very proud of project
2. MB: Excited about project and picking brain later, and getting arms around surveying customers and customer sentiment and institutionalize voice of customer program
   1. People run risk of thinking I’m taking over turf— but goal is reliability, and higher-level synthesis and seeing what we couldn’t see before and operational, and tactical decisions, versus cross-functional decision making
   2. Making clear not taking over data gathering process and making use of what we are doing well
   3. Early days and hope this will help reduce duplicative work and give insights
3. Thoughts on empowering collective versus few?
   1. RR: Beneficial, working across teams and marketplaces was establishing the thought process of the production line, and at end of production line and doing XYZ. Hamster-wheel
      1. Positioning research as strategic partners, can help answer the right questions and insight repository as huge game changer and pushing and provoking what do we already know
         1. Where do we need to start and new rich questions to answer and what other teams have answered and curators of knowledge at right starting block— as opposed to being at end of production block

RO: Sends lot of inspiration taking place from research leaders to other stakeholders and access to data that don’t need to be only one who builds it for credibility or value

1. Since leveraging AI, how you go about trying to educate stakeholders kindly and not solving every single one and be more thoughtful on collaborations in plural space
   1. RR: Not getting frustrated with constant research education for others, and focus on proper education and constantly evolving what research team is doing and making sure teams are interacting
      1. Making sure stakeholders partners, and it pays off in the end, and more time for other things — education pace is key and built-in for working with partners
      2. Understanding how to use it in, and how research benefits products
   2. MM: Leaning in on video to make sense of data with people querying repository and data science has done a lot to democratize access to data and made more tools and decision making to team with more and more insights
      1. Quotes from real users and video of how product works and how powerful it was and research on clips
   3. MB: At McKinsey went on journey and scaling UXR despite lack of data analysts and got pretty comfortable weaving insight from qual research into work and asking them to step up and measure and monitor progress
      1. Built out insights fluency model to understand how it worked, and dimensions for owning and accessing data and prioritizing what they learn and data leader available to others
         1. Model turned me from preaching to empowering people to go on journey themselves [though you need management buy-in] and figuring out people’s level of fluency and very powerful
            1. Took away guilt and shame
         2. Made it clear how organization would behave and operational and systematic and upped game
         3. We need to show what good looked like and helped them get there was important
   4. Have touched up on making insights more available and others to the table. Since we held to high expectations, don’t just throw everything, but how do we do this at scale? What role do we need to play to advocate for ethical practices in spaces in which we operate?
      1. RR: Fundamental to practice and at fullest level of ethics and ensuring PII and it’s protected
         1. Empathy is involved with every step of the process whenever humans are involved
         2. Need to grasp parameters and structures to protect people learning form and protecting people with right to exit interview and power to do so where not trying to control and get data, with understanding we are are at mercy of people we are trying to get and how are creating spaces where people feel safe to share info
         3. Be thoughtful of how we and others show up as researchers and doing a service
      2. MB: Especially with simple ways to make sure advocating for good ethics and consent statement in interview to let people know they can leave
         1. When making case for more participatory methods, and not just right thing to do, but good for business and demonstrating value gained from methods and practices and more inclusive
         2. Not industry problem — but diversify this for all entrepreneurs who want cloud computing and not just some
            1. Can build inclusive practices in without permission
      3. MM: Stands out to me where orgs don’t care and just don’t know in solace or comfort and feeling of being brushed off and other insights
         1. Data science has similar idea of what’s made
         2. Don’t know what will go wrong
2. What is one takeaways for positioning an insights organization within an org?
   1. MM: Embrace creativity and other ways to solve problems
   2. RR: Triangulate relentlessly
   3. MB: Welcome people in and create an inclusive experience for colleagues