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Description

Being simultaneously data-driven and creative seems paradoxical. So does building statistics into the creative process. John Paul de Guzman has managed to do both. As the founder and chief creative of Frost Design and Consulting Group, and speaker at the upcoming Design Ops Summit, millions of Filipinos have been impacted by their work with major FinTech and telecom projects. 

Much of the UX/UI talent in the Philippines is self-taught, often struggling with the gap between academic training and industry expectations. To address this, JP developed a systematic approach to training and design processes.  

JP and Lou discuss how Frost has embraced data-driven design, which, contrary to the creative chaos one might expect, has led to more efficient workflows and better client outcomes. By integrating tools like Trello and Figma, and leveraging AI for task management, JP has significantly reduced administrative overhead. This approach allows designers to focus on their work rather than getting bogged down in busywork. They can track work in real-time, eliminating the need for status meetings and improving overall productivity—a win-win for both the team and their clients.

 


What You'll Learn from this Episode:

 


Quick Reference Guide:

0:13 - Introduction of John Paul

2:16 - The path that got John Paul where he is today

5:18 - What it means to be data-driven

8:39 - Systematizing the data-driven design process by tracking workflows

11:58 - Mapping the workflow

16:01 - Break

18:45 - Tools for probabilistic analysis and managing time

24:11 - The level of granularity John Paul’s team tracks

25:56 - Handling aspects of work that are more conceptual and difficult to atomize

30:46 -  John Paul’s gift for listeners

Resources and Links from Today's Episode:

DesignOps Summit 2024 https://rosenfeldmedia.com/designops-summit/2024/ 

John Paul’s free boot camp for designers

 


Quotes:

“There’s a downside to having so much talent.” 

“When you add more people, quality starts to degrade.”

“It's because of the way we track this data and then use them to our benefit that we're able to understand not only the flow of the work but also the nuance of how the work is being done.”

“[Thanks to AI,] rather than tracking the work, we actually do the work.”

“The big advantage of this – nobody needs to ask what the status of the work is.”