CASE STUDY
Work Planner
Giving Supervisors Their Morning Back
ROLE
Lead Product Designer
Team
Two Principal Architects
TIMEFRAME
2024-2026
ROLE
Lead Product Designer
Team
Two Principal Architects
TIMEFRAME
2024-2026
ROLE
Lead Product Designer
Team
Two Principal Architects
TIMEFRAME
2024-2026
ROLE
Lead Product Designer
TEAM
Senior Project Manager, Principal Architects
TIMEFRAME
2024-2026
ABOUT THE PROJECT
OpenGov’s Enterprise Asset Management suite helps 2,000+ public agencies run their infrastructure: roads, parks, utilities, fleets, facilities. Inside every agency is a supervisor who has to decide, every morning, who’s doing what, with which equipment. In the legacy product (EAM Classic), the only tool for this was a bare “Task Calendar,” and the communities who relied on it most were exactly the ones it served worst.
Work Planner is an AI-driven scheduling tool that auto-assigns field crews to their daily and weekly work and lays the plan out as a “whiteboard,” a row for each person and each major piece of equipment, that keeps the supervisor in control.
It’s for field-operations supervisors and planners at agencies of every size (the heaviest Task Calendar users), across public works, utilities, facilities, parks, and fleet.
THE PROBLEM
Scheduling a field crew is deceptively complex. A supervisor isn’t dragging names onto a calendar; they’re balancing many moving parts with tools never built for it. Across a dozen agencies I interviewed, the same picture kept appearing: a physical whiteboard with sticky notes, a spreadsheet, or a verbal morning stand-up.
- Everything at once: Who’s available (PTO, sick days, shifts, skills, who can run which equipment), what equipment is free, and what work is due (priorities, deadlines, locations, real durations).
- Off-system and siloed: Plans lived on whiteboards and spreadsheets, disconnected from the asset and work-order data. One supervisor described his setup exactly: “I’ve started to use a whiteboard in my office. Every person has a different color for their name.” If the one planner was out, the operation slowed.
- Weather and emergencies blow up the day: A main break, a truck down, or a cold snap rewrites everything, and rebalancing is manual. Much of the work has hard weather limits, paving and sealing need a temperature window, and rain stops a long list of jobs outright.
- Scale: A single work order could be 1,000+ tasks (valves, hydrants, inspections) that all defaulted to the same due date and had to be spread across days and crews by hand.
- Built for analysts, used by supervisors: The existing Task Calendar and GIS-grade tools were too complex or too thin for non-technical field supervisors who just needed to plan the week. The ask was blunt: “I want one place to look at. I don’t want to jump from this platform to this platform to this platform.”
PROCESS
I ran a lot of interviews, fast. With an AI-assisted research loop I could interview several people, synthesize what I heard into personas and journey maps, turn that into a prototype, and bring it back for reaction in a fraction of the usual time, updating between almost each interview. I talked with agencies of every size and type, streets, utilities, facilities, parks, county and city, and all the pilot groups signed up to test the automation as it was built.
The most important thing wasn’t a feature request. It was a picture. Almost every supervisor, describing how they actually worked, drew the same thing: a whiteboard with a row for each person or crew and the days across the top. So instead of teaching a new mental model, I met them where they were and gave them the one they already trusted, with AI doing the heavy lifting underneath. I built interactive prototypes in Figma Make so the team and customers could click a real schedule and feel it at scale, and engineering built production from scratch with AI, because nothing off the shelf came close for us to mold into what we needed.
A company-wide demo I made of Work Planner and the AI-driven design and build process behind it.
EARLY IDEATION
An early Figma prototype, before the move to Make. I was working out how to show crews, equipment, tasks, and time all at once.
I explored several ways to show crews, equipment, tasks, and time together, from calendar to grid to labor view, before converging on the whiteboard. Enough to be useful at a glance, calm enough not to overwhelm.
SOLUTION
Organizing bet: Meet supervisors where they already work. Give them the whiteboard they already trusted, make it build itself, and keep the human in control: the AI proposes, the supervisor decides. The longer-term vision: shift supervisors from “manage everything” to “manage by exception,” where automation commits the routine plan and people only resolve the handful of cases that need judgment.
Design principle, “Think less, do more.” The clearest signal from the field was that supervisors don’t want to study a screen, they want to glance and act. So the design leans on bold, unambiguous visual states: locked work turns solid dark blue, capacity shows as a single fill bar, conflicts shout before they’re missed. Cards stay sparse (name and ID), and the customizable grid carries whatever details each supervisor cares about. Less reading, more doing.
The whole product in one view: a whiteboard with a swim lane per person and per machine, the AI’s overnight plan, drag-and-lock control, and the linked map, grid, and calendar.
- The whiteboard. A swim lane for every person and every major piece of equipment, days across the top. A task that needs three people and a truck shows up in all four of those lanes, so a supervisor sees who and what is committed at a glance.
- The AI does the first pass, you stay in control. The AI distributes the open work across days, people, and equipment overnight, honoring skills, availability and capacity, so the supervisor walks in to a plan that’s already built. They drag to rebalance and lock what they know is right; locked cards turn dark blue and the next run leaves them alone.
- Map, grid, and calendar, one linked surface. The board, the Esri ArcGIS map, and the customizable grid are the same data three ways. Supervisors can finally see and edit tasks on a map, cluster nearby work to cut drive time, and drop into the grid for detail.
Resource / Week / Month
Resource / Week / Month
One whiteboard, three lenses. Resource manages a person; Week and Month manage whole tasks at a glance, each tagged with the people and equipment it needs. Same controls throughout: select, then drag or use the menu to assign and move, even across several people at once. In Week view, shift whole days forward when the weather turns. “Give me all of this work and shift it by one day or three days, and it just automatically does it for you.”
Weather
A per-day forecast right on the board. Paving and sealing need a temperature window and rain stops a lot of work, so every agency wanted weather built in. One DNR team wanted river levels too, because the water line changes what work is possible that day.
Availability
Schedule Template Builder
The template-builder screen. Build reusable work-schedule templates for any day-cycle, not just a 5 or 7-day week. Crews on 4-on/3-off, or seasonal patterns get schedules that actually match how they work.
Schedule Template Builder
The template-builder screen. Build reusable work-schedule templates for any day-cycle, not just a 5 or 7-day week. Crews on 4-on/3-off, or seasonal patterns get schedules that actually match how they work.
OUTCOME
The live release is visually leaner than the prototype, and a few ideas got compressed to make the date. The grid was meant to do the heavy lifting for the minimal event cards, v1 keeps them to name and ID, but reveals the rest on click of the ID. Rich weather indicators, map selection, and the Week/Month views are rolling out next. It isn’t as polished as the prototype, but it held the principle, and it delivered.
In a pilot with 13 customers, Work Planner removed an estimated 80–95% of the manual scheduling work supervisors had been doing. The morning ritual that ate an hour or more became a quick review and a few tweaks.
The sell-forward team repeatedly said it demo’d better than anything else they had. New and existing customers kept asking when they could use it. Repeatedly. Work Planner launched publicly in 2026 as part of OpenGov’s AI-native Public Service Platform.
More than the number, what I’m proud of is the shape of the solution: we took something genuinely complex and handed it back to people in a form they already understood, with AI quietly carrying the weight they never wanted to carry.