Problem Statement:
Teamflow was already live in Helios, but there was very low adoption of the application. We tested the current design with users to uncover their painpoints and areas for improvement. Interviews revealed limited use of current Teamflow tool - manual workarounds were sufficient/provided more value. The product owners were aware of the lack of adoption and proposed some updates to help users, but were not satisfied in meeting their needs for priority portfolio + resource management needs.
We were tasked to reimagine the entire experience of Teamflow to provide value to managers and increase user adoption of the application. This required us to conduct user testing on existing designs, journey mapping to understand painpoints in their daily workflows, L2/L3 mapping of credit case creation and assignment within Helios, and understanding which metrics were vital for managers to assess team performance and workload.
Executive Summary
Here are some key screens from different versions of the Teamflow application.
Version 1: Current State (MVP)
The MVP was engineered as a centralized data repository to manage complex, multi-stakeholder credit review lifecycles. Given the high-density nature of corporate lending, the interface was designed to facilitate rapid triage across distinct user archetypes.
System Logic & Permissions
We implemented a Role-Based Access Control (RBAC) model where assignment logic is mapped to specific client permissions. This ensures team members are dynamically surfaced only for cases where they hold requisite authorization, maintaining strict data integrity.
Information Architecture (IA)
To reduce cognitive load, we included three strategic filtered views:
My Cases: Isolates high-priority active tasks for the individual
Team Cases: Aggregates the collective queue for collaborative squads
All Cases: Provides comprehensive system-level visibility
The primary interaction utilizes a deep-linking pattern; anchoring the Case ID within the data table allows users to bypass navigation and access granular details instantly. For management, we prioritized the visibility of "Assignment Gaps." By surfacing unassigned roles, the system mitigates the risk of bottlenecks in time-sensitive loan applications, ensuring compliance with strict operational SLAs.
Painpoints:
Lacking performance metrics to show priority, workload and case status
Sorting cases by overdue status to help with bottlenecks
Missing indicator for how long tasks are taking to be completed
Long list of data without any visual indicators to help sort data quickly
Missing temporary case assignment for unplanned leaves (vacations, sick days, corporate holidays etc.)
Version 2: Product's Next Feature (Role Assignment)
The 2nd MVP was a product-led directive to build a manual role-assignment feature. Stakeholders were set on launching a utility-focused table where managers simply linked team members to specific credit review roles. We knew this wasn't the right feature to build so we created a low fidelity prototype to test with users before investing design resources into the project. Our user research quickly exposed a critical gap: this feature alone provided zero incentive for adoption.
Our interviews revealed that managers weren't looking for another data entry tool; they needed an oversight engine. They demanded real-time performance indicators, workload distribution metrics, and task-duration tracking to prioritize high-risk cases effectively.
By surfacing this disconnect, we successfully pivoted the project from a "feature request" into a user-centric redesign. This evidence-based approach allowed us to move beyond basic role assignment and build a comprehensive dashboard focused on operational efficiency and risk mitigation—transforming what product "thought" was good into what users actually required to succeed.
Painpoints:
Missing case status at a high level AND task level
Focusing too much on case assignment and not the other performance KPIs managers need to distribute workload and bonuses
Not enough functionality needed to move away from excel sheets to this internal case management tool
Version 3: Strategic Pivot to Data-Driven Performance Monitoring
After surfacing that basic role assignment lacked sufficient value, we leveraged user insights and iterative testing to architect a performance-centric dashboard. The redesign shifted the focus from manual data entry to high-level operational oversight, providing the visual intelligence managers actually required to lead.
The final solution integrated dynamic data visualization, including:
Trend Analysis: Clear graphs and charts to distinguish between high-priority new applications and recurring annual reviews.
Real-Time Status Tracking: Visual indicators for active case progress and high-level summaries directly within the primary view.
Risk Mitigation: Integrated vacation indicators to alert managers of capacity gaps, allowing for proactive temporary coverage.
Improvements:
New performance graphs and charts showcasing case performance
New case details panel to show high level status and task completion
Vacation indicator within case chart to alert managers of temporary assignment
Improved case statuses to show what is overdue, how many tasks are complete, and which team members are assigned to different tasks within a case
Strategy and Decision Logic
The Constraints
Data Availability:
There were various statuses our users wanted to include such as team assignment for when cases would be handed off to different teams for QC approvals, task duration for how long it takes a team member to complete their tasks, and case complexity to flag when someone is working on 1 complex case vs. 10 smaller cases. Our development team couldn't make these available on the initial release, so it would take longer for them to build those datapoints into each case.
Component Availability
The design system doesn't have complex graphs to show multiple statuses such as progress bars, vacation time, and case details within pop-up tooltips. These were custom components requiring the development team to do custom coding. This extended the timeline a bit, but it was important for users to have this view.
Visual vs. Data
Many of our managers were already comfortable working with data dense excel sheets. Moving away from from data tables and into graphs and charts might be too much of a change for them, so we integrated a toggle to switch their view between the graph and data table design.
Collaboration
Product
We collaborated with the product team to audit backend data, mapping complex credit review roles to standardized UI components. By overhauling technical status labels into human-readable milestones, we translated raw system data into actionable context. This alignment ensured the dashboard reflected the user’s mental model, providing immediate clarity on case progress and team responsibilities.
UX Researcher
We partnered with the research team for a deep discovery phase to prevent investing in low-value features. By synthesizing user interviews into digestible research artifacts, we demonstrated the gap between stakeholder assumptions and actual manager pain points. This evidence-based approach successfully pivoted the business strategy away from manual entry tools and toward a metric-driven dashboard, ensuring resources were focused on solving real operational inefficiencies.
Wireframes
Our design process moved through three distinct phases, shifting from stakeholder assumptions to a validated, user-centric interface.
Design 1: The "Catch-All" MVP
The initial launch focused on a massive, manual data table for role assignment. While technically functional, it lacked a clear value proposition for busy managers, resulting in stagnant adoption and user frustration over "more data entry."
Quote from user:
"This feels like another administrative task added to my plate. I’m already underwater with reviews; I don’t have time to manually link every person to every role just to see who is doing what." — Senior Credit Manager
Design 2: The Logic-Check Prototype
We stripped the interface down to a low-fidelity prototype to test our "wrong feature" hypothesis. By presenting managers with simplified assignment flows versus mock data insights, we confirmed they felt the current tool was a liability rather than an asset.
Quote from user:
"If you’re just giving me a digital version of my spreadsheet, I’m not going to switch. I don’t need a place to 'store' names—I need to know which cases are at risk of missing their SLA because someone is on vacation." — Team Lead, Corporate Banking
Design 3: The Performance-Metric Dashboard
The final high-fidelity pivot replaced static rows with dynamic visualizations. We conducted a deep visual exploration to create a component library that prioritized scannable KPIs, case-type distributions, and vacation coverage alerts.
Quote from user:
"This is exactly what I’ve been asking for. Being able to see the split between annual reviews and new apps at a glance—plus knowing exactly where the bottlenecks are—changes how I run my morning stand-ups. It’s a tool that actually helps me manage, not just a table to fill out." — Operations Director
The Turning Point
Working closely with researchers, we mapped user pain points to a "Priority 1" feature list for the relaunch. We moved away from "assignment for the sake of assignment" and toward a command center that visualized team capacity and case status.
The Result: User sentiment underwent a massive shift. The feedback moved from negative frustration to genuine excitement as managers realized the tool finally automated their oversight needs instead of adding to their manual workload.
Final Impact
The Design Strategy:
Value-First Visibility
We shifted the primary objective from "data entry" to "data intelligence." By prioritizing high-level KPIs and at-risk cases at the top of the visual hierarchy, we ensured managers gain immediate situational awareness without digging through rows of static data.
2. Semantic Clarity & System Humanization
To reduce cognitive load in high-pressure environments, we replaced technical backend labels with human-readable milestones. Mapping these statuses to the user’s actual mental model transformed a "system log" into an intuitive narrative of the case lifecycle.
3. Progressive Disclosure for High-Density Data
To combat "scroll fatigue," we implemented a tiered information architecture. We utilized intelligent toggles for low-frequency fields, and collapsible panels to aid with information density.
4. Proactive Risk Mitigation
The design accounts for real-world staffing fluctuations. By integrating vacation and capacity alerts directly into the workflow, the dashboard functions as a proactive alerting system rather than a reactive record-keeper, ensuring strict adherence to operational SLAs.
User Adoption
Reduced manual tracking of cases and performance has increased user adoptions of automated tracking
Case Completion
Cases are no longer sitting in limbo due to missing team assignments
Overdue Cases
With the new case status labels, managers and team members are able to see which cases are at risk for being overdue and need additional team assignments
Increased revenue earnings
With the increased performance of case completion, more applications were being processed in shorter intervals
Key Learnings
The Business Outcome
By pivoting from a product-led "feature request" to a research-backed "user solution," we successfully transformed a low-adoption MVP into a mission-critical tool. The final dashboard didn't just organize data; it provided the operational intelligence needed to maintain strict lending SLAs and scale team capacity.
Key Takeaways
Data as a Diplomatic Tool: This project reinforced the power of research artifacts in stakeholder management. Using user evidence to "prove the pivot" saved months of engineering resources that would have been spent on a feature users didn't want
Designing for the "In-Between": I learned that true enterprise UX happens in the exceptions. Designing for vacation gaps and capacity shifts turned a static table into a proactive alerting system that solved a real-world business risk
Density is Not the Enemy: I discovered that professional users don't always need "simple"—they need "efficient." By using pattern mapping and progressive disclosure, we maintained high information density while drastically reducing cognitive load.