Client

Drug wholesale company

Deliverables

Prototypes, journey mapping, feature prioritisation

Role

Interaction & Service Designer

The Challenge

A global life sciences leader partnered with us to explore how AI, Gen AI, and AgenticAI could modernise their supply chain. The focus was on two pilots: replenishment forecasting, and inventory management. Our team was brought in to lead three workstreams: feasibility, viability, and desirability. I worked in the desirability stream, focused on understanding user needs and shaping what the future experience could look like.

Value Delivered

We helped a global life sciences leader turn AI ambition into action - aligning four VPs around a shared vision and securing a major follow-on deal. I led the design of forecasting tools that empower pharma buyers to better manage stock levels, cutting exception handling time by 25% and saving over $150K annually. Several of the features are now in build, supporting a projected $1B revenue uplift. The pilot is already helping reduce waste and prevent stockouts - getting life-saving medication to patients faster.

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Background

Our team began by interviewing Buyers and internal stakeholders to understand pain points across the supply chain. Together, we mapped the current journey, defined a to-be experience, and created a Buyer persona to align the wider team on user needs.I led the replenishment forecasting workstream from insight through to delivery. I created the to-be journey for this track, designed the prototype in Figma, and led the user testing sessions. I presented the work back to the client, gathered feedback, and iterated to sharpen both the experience and the story behind it.This project gave me the opportunity to apply a full set of design skills - from journey mapping and service thinking to UI design, prototyping, and user testing - while owning a core track of work in a high-stakes environment.

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Solution

We designed and prototyped a future Buyer experience powered by AI - one that would simplify planning, highlight risks early, and support faster decision-making. We ran multiple user testing sessions and iterated quickly, refining both features and flows to stay grounded in real needs. The final prototype was shared in a three-day client workshop, where stakeholders aligned and prioritized features for development.

AI meets urgency - reimagining supply chains to cut waste and get medicine where it matters, when it matters.