Transforming risk management from end to end
the client’s Challenge
An international management consultancy had a hunch to use technology to transform their risk analysis process.
What does that look like in practice? That’s where we came in to help. We immersed ourselves in their space, iterated, experimented, and delivered a solution which proved them right. Our product cut time needed for analysis in half.
My role
Lead Designer
Timeline
16 months
The Team
Build Team: Product Manager, Delivery Manager, 1 UI Designer, 6 Engineers
Client Side: Product Owner, Steering Committee of 12 Company Partners and Managing Directors, Liaison Committee of 40 Econometric and Statistical experts
Activities and Deliverables
Interviews, concept testing, continuous discovery, synthesis, wireframes, prototypes, hi-fidelity mocks, proof of concept in functional code which was piloted on a client engagement with a Fortune 100 client.
MVP
Envisioning a digital experience experts can rely on throughout client engagements
Research led us to conclude that for the tool to be useful and trustworthy, it had to offer analysts two modalities — Analysis and Translation — in one experience.
discovery process
To define this MVP flow, we undertook an extensive discovery process of interviews, observations, and rapid, lo-fi prototyping to understand current state and identify needs and opportunities.
feature
Instead of messy, buggy excel spreadsheets, build a model quickly, and cleanly
Previously, risk analysis models were created in confusing, difficult-to-decipher Excel spreadsheets. Our solution standardized this process, balancing convenience with quantitative rigor.
Design Evolution and Learnings
Initial designs, though sleek, didn’t communicate enough information to users. We learned they would have difficulty trusting a tool unless the calculations and assumptions were transparent.
Feature
Instead of static graphs and stale powerpoints, a platform for exploration and storytelling
design evolution and product strategy
To build a visualization dashboard we first had to align on a set of graphs and charts to support. In order to narrow down to a supported set of visualizations, we facilitated a workshop and asked participants to describe, in words, what each graph communicated. From there we successfully chose a robust set of charts to proceed with.
Impacts / Outcomes
Hypothesis → Prototype → Successful client engagement
hypothesis validated
Our product was successfully used on a client engagement with a Fortune 100 client who saved $1M in billable hours, successfully proving the initial hypothesis.
our work kickstarts ongoing collaboration
Additionally impactful, our team was retained by a separate area of the business and we went on to build a technology product to help streamline their process .