CASE STUDY

OTIS 2.0 — Modernizing Citation Workflows for the Ohio State Highway Patrol

Client: State of Ohio; Highway Patrol
Position: Lead Mobile UX Design and Research

The Problem:

Legacy patrol and citation software forced troopers to complete long, compliance-heavy forms in roadside conditions with unreliable connectivity. Unsaved work could be lost on refresh or device hiccups, leading some users to draft in Word as a workaround. Inconsistent ASP.NET screens and patterns increased error risk, slowed training, and eroded trust in the system. (Image: 17-Year-Old System to the right)

Heavy legal/jurisdictional data entry created a high cognitive load and rework.
Intermittent connectivity and unexpected refreshes caused draft loss.
Fragmented UI patterns reduced confidence and slowed onboarding.
Duplicate entry (people/vehicles) and limited validation increased errors.

Motorcycle Units, mobile UX: Citation Fulfillment

For motorcycle units, mobile UX must be glove-friendly, sun-readable, and operable with one hand, with oversized touch targets, clear feedback (haptic/audio), and offline autosave with background sync for quick-stop workflows. Our usability testing focuses on time-to-citation under realistic field constraints; based on recent lab and ride-along studies, practical gains over legacy flows typically cap below 30% improvement.

We design for that ceiling—streamlining steps, prioritizing high-frequency actions (e.g., plate capture, person/vehicle reuse), and minimizing context switches—so troopers see reliable, measurable time savings without risky complexity.

The Approach:

We paired field and ethnographic research with a design-system-first rebuild to make the experience reliable, recoverable, and learnable. Ride-alongs, interviews, and task analyses informed workflows. Fluent UI patterns with governed tokens/variables in Figma ensured consistency. A progressive data-entry model lowered the cognitive burden while preparing for analytics-driven iteration.

Ethnographic observation (ride-alongs), contextual inquiry, interviews, and journey mapping produced a series of Trooper Personas and Painpoints.
Fluent UI alignment with governed design tokens, variables in Figma, and component libraries.
Progressive data entry with clear status, inline validation, and error-recovery microcopy.
In-lab studies on how troopers enter data to search for efficiency opportunities in terms of troopers' data entry on an ongoing basis for all different citation types.
Instrumentation plan (time-to-complete, draft-loss, error hotspots) and offline-first strategy.

Figma Design System Variables types are ready for styles to export into design tokens for developers to export to Token Studio.

The fluent blazer design system is highly customized to the Ohio State Highway Patrol brand guidelines.

Accessibility Enhancements

Trooper Focused Accessibility Enhancements: A new landing page for in-vehicle use.

Our design system prioritizes legibility and fast target acquisition for a user base averaging 48–60, with ~80% of troopers over 50 using reading glasses.

Typography defaults to large sizes (18px body, scalable), high contrast (≥7:1 where feasible), and clear hierarchy to reduce squinting and re-reads in glare or low light. Interactive controls use oversized hit targets (≥44×44 px with generous spacing), bold focus/hover states, and concise labels for rapid confirmation at speed or during intensive data entry.

Components ship with “large/XL” density tokens so layouts can be upsized globally without breaking flow, and critical actions (e.g., submit, save, cancel) are consistently placed and thumb-reachable. The result: fewer errors, faster entry, and safer operation under real patrol conditions.

Image: NEW System Landing Page shown below.

One Master Form Field Component for thousands of form fields across the multitude of different citation types adding efficiency to a “skeletonized component library system.”

The Solution

We implemented event-based autosave/restore, an offline-friendly draft cache, and standardized patterns with smart defaults/prefill. Entities (people/vehicles) are reusable across citations, and visible save states rebuild confidence. Early signals show faster completion, fewer errors, and reduced reliance on third-party workarounds—setting a foundation for measurable gains in safety, compliance, and trust. 

Event-based autosave triggers: add/import person, add/import vehicle, license scan, attachment upload, jurisdictional change, step completion, plus periodic idle saves.
Offline draft cache with background sync and “Restore last draft,” preserving work through crashes/refreshes.
Standardized, tokenized patterns (review/submit, error states, forms) for consistency and quicker training.
Early outcomes: decreased duplicate entry, improved trust, faster onboarding; next metrics tracked—time-to-first-citation, draft-loss rate, and form error rate.

A refined, efficient workflow design for easy adoption and MVP approval.

The Impact

3x faster contract placement, reducing time-to-trade from weeks to days.
10–20% savings for buyers through improved transparency and matching.
Increased user confidence with AI-augmented workflows that simplified filtering and surfaced contract insights.
Established Tremor as a digital-first reinsurance disruptor during a period of record-breaking natural disasters (Hurricanes Ida & Ian, Winter Storm Uri).

>99.5% save reliability (target).

Previously, unexpected refreshes wiped work; event-based autosave + offline drafts now preserve every step and restore trust.

20–30% fewer form errors (target).

Inline validation, jurisdictional rules, and a review/submit step reduce rework.

25–35% faster to first citation (pilot goal).