Product Lead
Owned product end-to-end for an internal workflow platform: identified the problem, designed the UX, built the platform, and managed the 2-month change management rollout across 60+ team members. Automated client request intake, replacing a 3 to 4 hour daily manual process with ML-based classification and real-time team availability. Full adoption in 2 weeks, no mandate.
A Data Analytics team received 10 to 15 client requests daily through a shared inbox. Every morning, one person spent 3 to 4 hours manually opening emails, categorising each request across three service lines, checking an Excel tracker for availability, forwarding to the right team, and updating the file. When they were on leave, requests disappeared. Clients escalated.
I owned the product end to end: identifying the problem, designing the user experience, building the platform, and managing the 2-month change management rollout across 60+ team members including analysts, leads, and directors. A data scientist owned the ML model for service line classification.
We built instead of buying an existing SaaS tool.
Three reasons: cost was lower to build, we needed full feature control, and most critically McKinsey client data could not touch a third-party system. Privacy was non-negotiable. Building internally gave us data sovereignty, full feature control, and lower total cost.
Automated email intake
Pulls new client requests from the shared inbox every morning automatically. No manual checking, no missed emails, no dependency on one person.
ML-based classification
Each request is automatically classified into one of three service lines: Business Modelling, Data Engineering, or Predictive Analytics, using a trained ML model.
One-click assignment and notification
Assigning a request to a team member triggers an automatic email notification. Every request gets a unique ID. Leadership can search any request and see its status instantly.
Real-time availability dashboard
A dedicated page showing team capacity, current workload, and leave dates. Managers can see at a glance who is available to take new work before assigning anything.
The hardest part was not the build. It was the 2-month rollout against internal resistance. Directors who had managed via email for years did not want a new system. What I would do differently: involve the highest-resistance users in testing before launch. Their objections would have shaped the product and converted them into advocates.