Dashboard

5 minute read

A dashboard that learns what each user needs first

Active risk state. These signals only appear when thresholds are triggered.

The short version

I was asked to modernize WorkJam’s dashboard. Before changing the interface, I questioned what the dashboard was helping people do.

The usage pattern pointed to a larger opportunity: users landed on the page and quickly navigated elsewhere. The dashboard was a starting point in the product, but it offered little reason to stay.

I reframed the work around a more useful purpose: help people understand what needs their attention and get to the next action faster. I translated that direction into a working prototype, built support with product and sales leadership, and helped shape a focused first release using existing data and components.

The problem: a dashboard people moved past

The original brief, “modernize the dashboard,” described a change in appearance. It did not define the user problem or what success would look like.

The dashboard had no support tickets. On its own, that could suggest the experience was working. Combined with analytics showing users leaving the page for other areas of the product, it raised a different question: was the dashboard useful enough for people to rely on?

I treated the lack of complaints as a reason to investigate, rather than evidence of success. The opportunity was to make the page valuable within the flow of someone’s work.

The legacy dashboard. Every widget had equal weight. Nothing indicated urgency or risk. It functioned as a launchpad, not a place where decisions were made.

Strategic approach & collaboration

I identified the gap before a solution existed. Rather than inheriting the “modernize” brief at face value, I reframed the problem around decision-making, mapping manager behaviour and pulling usage analytics before a single screen was designed.

To make the vision tangible fast, I built a working prototype using v0 by Vercel and Lovable. Focused on one persona, built on existing platform data, with assistive AI surfacing risk signals directly in the interface. No new backend. No waiting for engineering.

I presented it to three audiences: VP of Product, Director of Sales, and Executive leadership, each framed around what they cared about most: platform strategy, competitive differentiation, and business outcomes.

What started as a subjective UI request became a formal 0→1 initiative with executive sponsorship, a 2.5-sprint plan, and full cross-functional alignment.

Vision prototype built with v0 and Lovable, used to align leadership before a single sprint was planned.

The solution: A modular decision surface

I delivered a 0→1 dashboard system that moved beyond static reporting into proactive decision support. Rather than presenting raw metrics, the dashboard prioritizes signals that indicate risk, opportunity, or required attention.

The core design challenge was deciding what deserved attention on the primary surface and what should stay out of the way, making deliberate choices about hierarchy, signal visibility, and when the interface should speak up versus stay quiet. The system was built modular from the start, so different personas could focus on what mattered to them without redesigning the foundation.

Design decision: Risk pattern

Two valid options: make risk always visible and risk alarm fatigue, or surface it only when triggered and risk managers missing it.

The job-to-be-done settled it. Managers come to the dashboard to answer one question: “What needs my attention right now?” Risk needed to be findable without being loud.

The solution was a hybrid: a consistent attention area that stayed in the layout but only expanded when thresholds were triggered (late punches, unapproved timecards, coverage gaps). Validated through manager feedback, prototype click behaviour, and engineering feasibility.

Risk signals surface only when thresholds are triggered. Each card explains the problem, the impact, and the next action.

Quantifiable impact

Competitive

impact

Became the hero experience in enterprise sales demos, helping visualize the platform’s future-state intelligence and improving win confidence.

80%+

adoption rate

Adoption was immediate across active accounts, elevating the dashboard from a “nice to have” to an active, multi-phase roadmap initiative.

~10

minutes saved

Managers could quickly understand workload, risk, and priorities without manually scanning multiple sections or reports.

Scalable

foundation

The system was built to scale from today’s operational insights to future intelligent guidance as usage patterns evolve.

How we validated these results

Impact was informed through a combination of product analytics, internal benchmarks, and qualitative feedback from managers and go-to-market partners during rollout and sustained usage. Results reflect aggregated patterns observed across roles and workflows rather than isolated outcomes.

Why this matters

This dashboard established a decision-support foundation that later enabled deeper operational experiences, including Manage Schedule. By treating the dashboard as an entry point for understanding risk and opportunity, subsequent features were able to act as focused decision layers rather than isolated tools.

Together, these initiatives reflect a consistent platform strategy: turning complex, interconnected data into clear, actionable guidance at the moment decisions are made.

* A note for recruiters & hiring managers

This case study is a high-level overview of my process in navigating ambiguity and driving cross-functional alignment. To keep this scannable, I’ve omitted the granular details of the technical architecture, iterative prototyping, and specific accessibility audits.

I would be happy to walk you through a deep dive of this project during a 1:1 interview.

Quick wins

Previously invisible operational constraints were surfaced directly in context, helping managers understand why certain metrics or risks mattered. This reduced reactive investigation and enabled faster, more confident decisions without adding new data sources.

Rather than functioning as a standalone reporting surface, the dashboard became a coordination point across operational domains. Signals from staffing, compliance, and workload were translated into a shared decision context, unlocking value from existing systems without requiring structural changes.

By prioritizing clarity and early risk visibility, the dashboard addressed common reasons managers relied on spreadsheets or offline tracking. This helped restore trust in the platform as the primary source for operational insight.

Focused on surfacing only the most relevant signals at the right moment, allowing managers to act quickly without navigating deeper configuration or secondary reports.

Role

Roadmap influence

Product strategy

UX architecture

UX and UI

Team & Partners

VP of product • Sponsor

Dir. of sales • Strategy

Architect • Logic

Lead engineer • Dev

Senior designer • Lead

Duration

  • Phase 1: 2 Sprints (MVP)
  • Phase 2: In Development (Scalable framework)

Hello,
I’m a product designer with over 10 years of experience creating solutions that drive real business results.

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