Boost Workflow Automation
This project focuses on designing an intuitive interface for the “rules” engine of a workflow automation tool, tailored for financial institutions. These organizations rely on complex, logic-driven processes for tasks like fraud detection, compliance checks, and transaction approvals. The rules engine enables users to automate conditional logic at scale—ensuring accuracy, consistency, and regulatory compliance. By simplifying the creation and management of these rules, the design empowers both technical and non-technical users to build adaptable workflows, reducing errors and increasing efficiency across financial operations.
Project Duration
October 2022 - December 2022 (3 months)
The Problem
Employees struggle to manage complex, workflows due to lack of intuitive tools for creating and maintaining conditional rules
Role
Designer & Researcher
Responsibilities
User Research, Prototyping
Research
Understanding user needs and pain points was critical to designing an effective rules engine for Boost workflow automation. Conditional logic plays a central role in complex financial processes, but users vary widely in how they approach and manage these rules. Because both technical and non-technical staff contribute to building and maintaining workflows, we needed to explore their distinct challenges and expectations. To do this, I interviewed 20 users with varying levels of experience in working with conditionals. These conversations revealed key patterns and pain points that shaped a more intuitive and accessible design.
What is wanted in the Rules Configuration Component?
Less technical
Allow users to define rules using plain language or through step-by-step prompts that translate into logic, lowering the barrier for non-technical users.
Rule previews
Visual previews or flowcharts that show how rules will execute in real scenarios, helping users understand the logic before deploying it.
Contextual Help and Tooltips
Inline guidance, such as tooltips, examples, or short tutorials next to complex fields or actions, to reduce user confusion and mistakes during rule creation.
Validation and Feedback
Immediate alerts or suggestions when a rule is incomplete, conflicts with another rule, or might violate compliance standards.
Who are we designing for?
Developers who are more familiar with logic and conditionals
Goal: Users want to use Boost to easily configure rules so that their processes can be automated more efficiently
Pain point: Previous method of rule configuration is difficult and inefficient
Non-technical business users
Goal: Users need a clear and understandable way to create rules for their processes
Pain point: Previous method of rule configuration provides little to no guidance for users who are new to Boost or less familiar with the concept of rules, and uses language/symbols that are inherently confusing without a technical background
Solution
Enhance rule configuration in Boost with a design that bridges the gap between technical and non-technical users, simplifies rule creation without sacrificing power, and
increases confidence with easy testing.
User Flow & Wireframes
To design an effective and accessible rules engine for Boost, we began by mapping out how users conceptualize and build conditional logic. This process was guided by user research and focused on understanding how rules are structured, triggered, and maintained across different levels of technical expertise. The wireframes reflect the visual hierarchy and flow of logic, breaking down complex rule structures into manageable, intuitive components. Meanwhile, the user flows detail the step-by-step experience of creating and modifying rules.
Designs and Prototypes
The final design is a significant improvement from the previous version of the rules engine in Boost, both in functionality and user experience. Where the original interface was dense and difficult to navigate (especially for non-technical users) our redesigned solution introduces a far more intuitive and flexible approach to building logic. Visual clarity, contextual guidance, and real-time feedback now make it easier for users to understand and construct complex rules. The addition of features like paths, groupings, rule previews, and the formatting expression modal have made the user experience more streamlined and accessible. This redesign improved usability across diverse user groups and increased overall confidence in using the platform.
Old Rule Configuration UI
New Rule Configuration UI
Next Steps
Conduct longitudinal usability testing to observe how users interact with the rules engine over time and identify areas where confusion or inefficiencies persist.
Introduce inline AI assistance to help users write or troubleshoot rules using natural language prompts, especially for non-technical users
Enhance collaboration features such as notifications and shared editing