Context, Curiosity, and Cutting Through the Noise with Qun Wei (Lemonade)

How modern data teams can lead with context, curiosity, and clarity. Lessons from Lemonade’s VP of Data Analytics, Qun Wei on Crunching Data.

Sarah Lubeck

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When Qun Wei builds modern data teams, he doesn’t start with tools or dashboards. He starts with trust.

On this episode of Crunching Data, Qun, VP of Data Analytics at Lemonade, shares how his team scaled alongside the company’s growth. He also opens up about how he evaluates tools, where self-service breaks down, and why context in data analytics is more important than ever.

If you're leading a modern data team or thinking about your data strategy for 2025 and beyond, this episode is a must-listen.

Here are some areas we dive in:

The future of modern data teams isn’t dashboards

Dashboards are no longer the gold standard. According to Qun, they’re just one possible surface area for insight.

“You don’t want the dashboard. You want someone to tell you what is going on, what you should do.”

He believes data teams need to focus less on visualizations and more on delivering clear, actionable insights. This shift is especially important as AI reshapes expectations around data accessibility and speed.

Context is the hidden advantage in data analytics

One of the biggest takeaways from this episode is how overlooked context remains in most data teams.

“The data that lives without context is very hard to [use], especially when there is business context to the data — a very specific business context.”

Qun argues that access alone isn’t enough. Context in data analytics is what allows teams to bridge the gap between numbers and decisions. And without it, even the most beautiful dashboards fall short.

Self-service is not always the solution

“Just because someone can self-serve data doesn’t mean they should… You also don’t want everyone to become a data analyst.”

Self-service BI tools promise accessibility, but Qun pushes back on the idea that every stakeholder should also be a data analyst. Instead, modern data teams should create leverage for others — not replicate themselves across the org.

How Qun evaluates data tools

With new vendors launching every month, data leaders are bombarded with options. Qun recommends a back-to-basics approach to data tools evaluation:

He emphasizes choosing tools that solve specific problems and integrate naturally with your workflows, not tools that impress with long capabilities lists. Side note: We're pretty happy Matia is on Lemonade's list.