Expert Network · 2025
I joined an expert network platform where project managers spent hours manually reviewing expert profiles, cross-checking availability, and negotiating terms of engagement. Every new project required back-and-forth emails and spreadsheet tracking. I was brought in to redesign the sourcing workflow end-to-end — simplifying matching, structuring agreements, and cutting out the manual overhead.
Problem area
Project managers were drowning in repetitive, high-friction steps. Finding the right expert meant scanning long lists, checking profiles one by one, and then negotiating terms over email. There was no structured agreement flow — everything was ad hoc. This led to slow turnarounds, misaligned expectations, and clients losing confidence in the product.
Automate the expert-client matching workflow to surface the right profiles faster and eliminate manual scanning.
Introduce a structured Terms of Engagement flow that gives both sides clarity and speeds up agreement signing.
Design goals
Surface the right experts faster by reducing cognitive load and removing repetitive manual steps.
Give clients clear terms and expert credentials upfront, reducing hesitation and renegotiation later.
Cut sourcing time by automating the repetitive steps between finding an expert and finalising an engagement.
Design decision 01
Research showed matching quality was the top driver of client satisfaction — and the top source of frustration. I focused on a relevance-first profile layout and a smart filter system that made it obvious which experts fit a brief, without requiring deep manual review. Relevance scores, availability badges, and key credentials were brought to the surface so managers could decide in seconds, not minutes.
Average sourcing time dropped from 4–6 hours to under 90 minutes
First-suggested experts were accepted 70% more often after redesign
Design decision 02
Terms of engagement were previously negotiated ad hoc over email. I designed a guided flow that walked both parties through scope, rate, availability, and confidentiality — with clear defaults and inline explanations. This reduced back-and-forth and gave both sides a shared record of agreed terms before any engagement started.