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The Dock, Accenture · Jan 2025 · 5 min read

Decoding Healthcare

RoleInteraction Designer
Team2 designers, 2 data engineers
Duration7 weeks
DeliverableData storytelling sales tool
OutcomeStatic deck replaced — in active use; team flown to the US, second client round requested

Two teams who never spoke to each other, building a product that had to work in a room with a client.

Problem statement

The client used data analytics to win business: showing potential buyers where risks were rising, which programmes would help, how much they'd save. The data was strong. The problem was that the sales team couldn't explain it and the data team didn't know what the sales team needed to say. They were rarely in the same meeting. The tool they were pitching with was a static deck.

The entry point screen on iPad. A dramatic illustrated hero — a silhouetted figure with binoculars set against geometric navy and teal shapes — with the headline "Stay Ahead With Predictive Insights" and a "Predictive Data Insights" CTA. The tool had to explain its promise before a salesperson had to pitch it.
The entry point screen on iPad. A dramatic illustrated hero — a silhouetted figure with binoculars set against geometric navy and teal shapes — with the headline "Stay Ahead With Predictive Insights" and a "Predictive Data Insights" CTA. The tool had to explain its promise before a salesperson had to pitch it.

My role

I owned the design end to end — chart library, collaborative annotation layer, and an opening experience designed to frame what the tool was for before any data loaded. One frontend engineer handled the build; three data engineers managed data fetching and the environment setup within Accenture's infrastructure. The design brief was effectively mine to define: the client hadn't separated sales needs from data needs before, so there was no existing spec to follow.

Process

I started by sitting with each team separately — the data team explaining what the models could show, the sales team explaining what they needed to say in a room with a client. They rarely met together. Most of the work wasn't designing screens. It was narrative architecture: translating between two domains without ever having both in the same room at once. I anchored on the sales side. What could a salesperson actually say in a meeting? What did they need the data to prove? I worked backwards from those questions into what the interface had to show.

The direction changed significantly mid-project. We started with a narrative about one individual moving through their healthcare journey — relatable, but too narrow. I took that feedback and restructured around it: existing clients would see their own real numbers, prospective clients a representative book of business. That shift changed how the story was structured, how the charts were annotated, and where users could dive deeper or skip entirely depending on who was in the room.

Cost per member, per month predicted for the next 12 months, shown as a horizon chart. Two overlapping waveforms on a dark background: blue for the client's projected spend, yellow for the book-of-business benchmark. Both converge toward a $22,000 ceiling at the right. The legend sits at the bottom. The deviation reads in a single glance.
Cost per member, per month predicted for the next 12 months, shown as a horizon chart. Two overlapping waveforms on a dark background: blue for the client's projected spend, yellow for the book-of-business benchmark. Both converge toward a $22,000 ceiling at the right. The legend sits at the bottom. The deviation reads in a single glance.

I tested with the sales team throughout. They were one of the two audiences I was designing for, and what they could and couldn't use in a meeting shaped every decision.

The SDoH chart went through more than a dozen versions. Early cuts were simple: a bar chart of the most common factors, S-curves mapping risk escalation by category. Clear, but they didn't show the relationship between conditions and social factors. We tried stacking more in — area charts layering member counts and cost, trellis grids with every condition and SDoH factor labelled. A diamond correlation matrix showed all of it at once. The data team could read it. No salesperson could have narrated it in a room. We landed on a sunburst: filterable by condition, each SDoH factor as a ring, the key risk level readable at a glance. The constraint that shaped the final choice wasn't what the data could show. It was what someone could say out loud.

SDoH chart iterations — from left to right: S-curves mapping risk escalation by category; a diamond correlation matrix plotting every condition against every SDoH factor; and the sunburst that made it into the tool. The sunburst is filterable by condition, each ring is a SDoH factor, and the key risk level reads at a glance.
SDoH chart iterations — from left to right: S-curves mapping risk escalation by category; a diamond correlation matrix plotting every condition against every SDoH factor; and the sunburst that made it into the tool. The sunburst is filterable by condition, each ring is a SDoH factor, and the key risk level reads at a glance.

Outcome

The tool is actively in use. The team was flown to the US to present it to new stakeholders. A second round has been requested.

The Commercial Sales Leaders said they could speak about it for four hours. The Data Team Lead told everyone how quickly it came together. The CTO said it helped them get to where they wanted to go faster.

Stakeholder feedback collected after the US presentation. Three speech-bubble cards in warm yellows: "We're super excited to show this to people! I could speak about it for 4 hours." — Commercial Sales Leaders. "I have been telling everyone how impressed I was at how quickly it came together." — Data Team Lead. "The tool you built helps us get to where we want to go faster." — CTO.
Stakeholder feedback collected after the US presentation. Three speech-bubble cards in warm yellows: "We're super excited to show this to people! I could speak about it for 4 hours." — Commercial Sales Leaders. "I have been telling everyone how impressed I was at how quickly it came together." — Data Team Lead. "The tool you built helps us get to where we want to go faster." — CTO.