Research Democratization: Reframing the Conversation - from Training to Decision-Making

Organizations' appetite for UX research has grown over the past few years. Stakeholders and leaders are becoming more aware of the need to have research as a capability within their companies. However, the appetite to build a research discipline isn’t always matched with a comparable level of investment. This misalignment has led to the conversation surrounding research democratization – scaling UXR skills by training non-researchers to become apprentice researchers.

This has been a contentious discussion for a while now. The research community is divided by the topic. Some see this as a devaluation of the profession; others see it as an opportunity to build awareness and do more with less.

As a UX research manager involved in leading democratization efforts in 2 companies, I can see both sides of the argument. However, in my experience, there is no one size fits all approach. Company culture and UX design maturity play a big part in the success of these efforts.

In the following article, I unpack the argument surrounding democratization by surfacing stories from the industry and my own experiences. My goal is to help guide those thinking about embarking on a democratization effort by asking them to think more broadly about the long-term goals of the research practice within their organization.

Teams exposed to good research practices are better equipped to generate, internalize, and interpret research findings. Building these research muscles helps expand the dialogue and elevate the practice – creating a culture of evidence-based decision-making. I’ve experienced varied success levels here, largely dependent on the level of support from leadership to train non-researchers and the commitment from the non-researchers to immerse themselves in learning new skills.

Teams that immerse themselves in the research practice become advocates not only for their research findings and amplifying these through the organization but also for the nuances in the craft within good research: methods, planning, recruitment, and synthesis rigor. For example, when supporting multi-disciplinary teams running both generative and evaluative studies, I witnessed people become instantly more interested in research best practices and develop a deeper respect for the practice.

Not all research questions have the same level of risk or ambiguity and therefore require the same level of skill. A common approach for organizations with limited research experience is to offload the low-risk work to non-research team members. For example, I’ve helped non-researchers run narrowly defined usability tests informed by prior generative research.

If you’re unsure about your project's risk level, Jeanette Fuccella outlines a framework for assessing research risk and problem clarity.

Training non-researchers is a very attractive solution when you have a resource-constrained team trying to move quickly. However, organizations that ask amateur researchers to provide insights without the appropriate level of oversight run the risk of generating poor-quality insights. Poor UXR rigor and low-quality insights can erode trust in a UXR practice or lead to poor decision-making.

For example, teams are more likely to make mistakes without a thorough training program and the right level of oversight. Here are a few examples of where things can go wrong:

• Selecting methods that aren’t suitable for the research question.

• Conducting evaluative studies in place of generative studies.

• Not recognizing unchecked biases.

Generally speaking, researchers are uniquely equipped to empathize deeply, check their biases, navigate ambiguity, and cultivate curiosity. Unfortunately, these traits don’t come naturally to everyone.

For example, extensive synthesis work can be daunting for new researchers. Making sense of vast amounts of unstructured data is challenging, and it’s not uncommon for amateur researchers to find themselves in analysis paralysis. Another issue I’ve experienced with non-researchers doing synthesis is that they are uncomfortable with the ambiguity that sense-making can involve. As a result, they are prone to synthesizing findings with their own confirmation bias – looking only for insights that support their existing ideas.

Saswati Saha Mitra, Research Director at WhatsApp, has some very insightful learnings to share about her efforts to democratize research. She spent 1.5 years developing a Research Champions program to train non-researchers, only to learn that:

Product teams (especially in a startup environment) are famous for moving quickly and being scrappy, and when it comes to research democratization, the incentives don’t align.

When starting a research practice, I’ve found that designers and product managers show a lot of enthusiasm for learning and joining listening sessions in the beginning. However, it doesn’t take long before they realize they don’t have time to fully invest in the craft (on top of their day-to-day responsibilities).

Furthermore, democratization efforts don’t offer official incentives for non-researchers to become researchers. Team members are measured and compensated based on their core job function, which means research learning gets deprioritized. It’s unfair to ask people to take on two roles.

In my experience, it’s not uncommon for people to conflate good research with access to research software. This can lead to pressure from leadership to train non-researchers in research tools to upskill the team. Templates and software are tools that support experienced researchers to move faster, but it’s misguided to assume they will replace the skill of an experienced researcher.

The following are techniques I’ve found helpful when socializing research insights throughout an organization.

• Exposure hours/ listening sessions - invite team members to ‘sit in’ on live research sessions or listen to recorded research interviews, customer service calls, etc.

• Shadowing program - design a program where people across the organization can observe staff members.

• Workshops - synthesis workshops or work sessions are a great way to immerse the team in the raw data.

• Socialization strategies - share insights in a format and channel that aligns with the organization's culture. Presentations, interactive sessions, lunch and learns, quizzes, newsletters, insight nuggets, and full reports.

• Repository - build a central archive of research reports and raw findings for the organization to self-serve.