Case Study / Product Modernization
Role
Lead Product Designer
Users
Operations managers and schedulers
Scope
User research, service blueprinting, interaction design, AI-enabled prototyping, testing, delivery
Timeline
18 months
Status
Core workflow shipped; additional scheduling and AI capabilities in progress
OVERVIEW
WT and TG have been staples of TEAM Software since 1989, supporting security & cleaning companies with their financial management, workforce scheduling, attendance, and service delivery in both North America and the UK. There was never a designer on the team, and over the decades, incremental updates had left both products in need of more than a visual facelift. My challenge was to address longstanding user pain points, improve usability, and modernize the experience while preserving the familiarity and efficiency our power users relied on.
OUTCOMES
Saved on average as measured by post-launch analysis & user feedback
Schedule-building measured across 12 users using the bulk-editing workflow
To fill 5 shifts after bringing in bulk editing capabilities. Same result, less backtracking
Disclaimer
THE BUSINESS & USER PROBLEM
Modernization a workflow built around legacy software
The product contained decades of business rules, workarounds, and expert habits. New users struggled to understand it, while experienced users depended on familiar colors, layouts, and keyboard-driven behaviors to work quickly. For years our users were promised modernization, but never delivered. I was brought on to modernize the schedule boards of both products, from discovery with users to implementation.
New users
Struggled to learn the product and it's dated patterns
The business
Risked losing existing customers to more modern competitors, and having a hard time attracting new business
Power users
Depend on familiar patterns, short cuts, and depth of complexities
Schedule board UI
This slider shows the legacy schedule board and my modernized version as it is today. I introduced progressive disclosure, met WCAG standards, and relied on existing icons and color to convey data in one, clean experience.
Built a library of patterns
I smoothed out confusing patterns that exist in our legacy product, and introduced consistent, repeatable patterns throughout the modernized web experience. This included creating pattern definition documentation to define how we were modernizing across the entire product.
Legacy
One field, multiple behaviors. A single interaction could open different containers depending on whether a user clicked once or twice. This is just one example of the complexities that exist in the legacy product, patterns like this had accumulated across hundreds of screens.
Modernized
I introduced side sheets that follow a pattern library allowing for tabbed side sheets if certain data needs multiple instances. The side sheet has been reused on the majority of screens and is a predictable, repeatable component/pattern that one could expect.
Customer feedback
MY ROLE AND CONSTRAINTS
I worked in a "Product Triad", meaning one PM, one engineer, and one designer (myself). We collaborated through a large chunk of the process, from brainstorming sessions, user discovery, interviews, co-creation with our users. While I worked independently on building and maintaining the service blueprint, JTBD flows, interaction designs, rapid prototyping, and composing the design hand-off for engineering. If you're interested in reading more about how I collaborate with the product triad: Empowered Product Teams
The main constraints I had to work with:
Technical / Legacy
Business / Timeline
Resource / Data
Compliance / Accessibility
DESIGN DECISIONS
Three decisions that made modernization possible
Like every good project, there are design trade-offs that need to be made. Below are only some of the deliberate compromises that moved the product forward without losing sight of the user.
Decision 1: Preserve the signal users already trusted
Legacy
Modernized
Ex: Schedule card
Legacy uses color-coded symbols to represent 15 schedule-card attributes. I retained their placement, improved WCAG compliance, and added icons and badges for clearer identification.
Decision 2: Organize complexity instead of hiding it
Ex: Permissioning
I replaced legacy page-by-page checkboxes with reusable permission roles and a hierarchical toggle system, allowing managers to apply permissions to multiple users and make bulk changes with ease.
Legacy
Decision 3: Turn repetitive scheduling tasks into bulk actions
Ex: Bulk actions & multi-select
Survey participants called repetitive tasks “a waste of time.” I addressed this friction with multi-select and full-shift copy/paste, reducing workflow steps without changing the outcome.
Legacy
Modernized
THE REDESIGNED WORKFLOW
I redesigned workflow brought contract creation and schedule filling into a clearer sequence, reducing back-and-forth while preserving the rules that power users depended on.
Create or configure the contract: Allowing a user to quickly create contracts by copy/pasting individual fields, entire rows, or an entire week. Speeding up contract creation as many users have given evidence of the repeatable nature of contracts. Below is a prototype to showcase bulk editing.
Editing and maintaining the working schedule: Allows our users to balance their day-to-day schedule, replace workers who have called out, optimize for future weeks, or review incidents that occurred on past shifts. In the legacy software, users have to jump around from screen to screen, I wanted to bring all the complexity without ever having to leave the main screen.
Bringing in AI to our schedule board: The precursor to bringing in an AI Agent was creating algorithms to optimize a schedule and surface the most suitable employee based on lowest cost, lowest overtime, or other criteria. Thanks to the work I did on permissioning and workflows, the engineering team was able to build an algorithm that worked with my designs. This was the starting point for our AI Agent, to read more, head over to this case study
VALIDATION AND ITERATION
I tested the workflow with operations users and schedulers, combining interviews, task walkthroughs, survey analytics, and prototype feedback. The research did not point to one perfect answer. Once I had enough data to confidently make a decision, I was able to capture the features most heavily sought after, that met the business goals, and my users' goals. I also got a feel for their trust in AI, as that was coming to the schedule board, and I wanted to test some prototypes early with them.
THE FINAL RESULTS
Faster work, fewer clicks, promises kept.
I heard incredibly positive user feedback, the business saw an uptick in bookings and projected revenue after showing these features off at the latest user conference, and our customers are finally feeling like the promises they've been hearing are being kept.
TAKEAWAYS
What this project taught me
Modernize without erasing expertise.
Make complexity legible, not invisible.
Balance evidence with the reality of delivery.