Trend Engine
User research and a roadmap for a tool that helps fashion brands spot trends and decide what to make, using data and AI.
The problem
Li & Fung, a Hong Kong company that runs supply chains for fashion brands and retailers, was bringing the apparel supply chain online, from first concept to delivery. The Trend Engine was the start of that chain: a tool to help brands decide what to design and buy.
Trend research was slow and manual. Designers, buyers, and merchandisers browsed shopping sites and trend services by hand, and backing up a trend call was hard.
What I did
I ran the user research. I interviewed research and development staff, merchandisers, designers, outside buyers, and planners, and turned what they told us into personas and a clear list of pain points.
I ran a product alignment workshop to agree on the vision and goals, then set a roadmap in stages: first bring products and trends into one place, then analyze the trends, then use AI to recommend what to make, with each stage feeding Li & Fung’s other apps.
I also reviewed how the development teams worked and wrote a plan to standardize Scrum across them, with a shared workflow, a common definition of done, and a rollout plan.