Hi, my name is Manlo Ngai, a multidisciplinary designer based in Orange County, California. I work with agencies, startups and the world’s most relevant brands. I have had the extreme privilege to collaborate with the best who help each other to raise their games. My hobbies bounce from personal art, 3D printing, game design to AI technology.
My view includes working in a start-ups and large corporations, but usually in an agile environment. I describe the term of users and customers depends on the stage of the business.
Frame the problem. What’s the market potential, competitor analysis, and understanding of your customers and their motivation.
Is your product solving the right problem? A hair on fire problem? A vitamin or painkiller?
I empathize and listen to users’ struggle, gather key insights from diverse perspectives.
Define use-cases and user journey. Who is for, why is it matter?
Identify pain points, uncover the “jobs-to-be-done”.
Understanding the ‘why’ behind user needs, wants and different touch points in the customer’s journey.
Define the OKRs or metric that matter to the business early.
Generate LOTS of ideas from different perspectives and refine to the essential few solutions.
Sketch on paper, whiteboard, or digital mocks for specifications (principles, guidelines, colors, typography, iconography).
Make it look good! Think of various layouts, UI and interaction to provide the desired experience.
Get buy-in across your group and involve with stakeholders into the design process early.
I am proud of my rapid hi-fi comps to help visualizing what the team is thinking and bring people to decision faster. As for the digital product, it’s better to make an interactive prototype and get early feedback before user testing.
Involve engineers early to see what’s possible with the latest trends and practices.
Synthesize the feedback, do a post-mortem to evaluate results and share learning across the team within the company.
Is it easy to use for the end user? Does it provide the desired solution to user’s problems?
Keep learning and use data/evidence to guide the next iteration.