Allison Milchling. Product Designer.


REVIEW. Leveraging Machine Learning.

Project Summary

Captricity’s core product automated insurance workflows by using machine learning to digitize handwritten data from paper forms. However, it was not yet an end to end solution. The offering contained a major workflow gap that caused duplicate efforts and a large portion of digitized data to be thrown out. We needed a way to store partial data to be repaired so that higher throughput could be accepted downstream.

The result is an isolated, UX-friendly interface, “REVIEW”, in which data entry clerks can log in and review digitization results. They can edit values using the “human” resources unable to be hardcoded into Captricity’s models. The result of this tool is more cases being accepted with a fraction of the manual effort.

As the company's sole designer, I vetted and championed the problem with a junior PM and owned the end to end UX of this project. I worked side by side with a scrum team containing 6 app engineers and consulted with 2 MLEs throughout the project.

The Problem

Inefficient workflow creates a bad customer experience:

Testing and User-Centered Development

Consistent feedback for iterative design:

User journey mapping:

One of the biggest concerns for this project was whether or not our small, young team was capable of launching a completed V1 product in a three month deadline. The user journey mapping artifact I created provided the following benefits that were visible throughout the project:

Final Design and Resolution

Captricity’s machine learning technologies are so advanced because of our foundational understanding that human input is required to achieve the best results. REVIEW gives users a place to review and repair invalid forms, providing the following value:

Main Takeaways

Launching an alpha product was a very critical strategic initiative for Captricity, and the REVIEW launch at MetLife would not have been possible without the user-centered design focus that I employed. My contributions to the project went beyond delivering a functional and intuitive UI - I created a transparent, open culture within the scrum team to drive everyone to efficiency, I iterated on the design to fit the available scope, and I engaged users diligently for feedback but filtered through just enough to create a great UX without pushing back the timeline.

From a marketing and sales perspective, the alpha went well. Within the first few months, MetLife was seeing 35% higher throughput volume - a 50% increase over the initial success metric we had agreed upon. They renewed and agreed to a press release.

Since the release I have improved the design for higher complexity use cases. I’ve been heavily involved in the transition process as customers decide to change their monolithic workflows to choose smart, lean UX and adopt REVIEW. Standing by the current state of the product and assessing feedback to shape its future directly with customers has been a delightful challenge.

Other Work

Partner Portal. Enterprise Architecture.

Data Configuration. Autonomizing Workflows.