WorkMark —
Performance Clarity Dashboard
"Leave your mark every day."
Designed to replace memory-based performance evaluation with evidence-based recognition — without increasing cognitive or political burden.
See WorkMark in action
A walkthrough of how WorkMark captures contributions automatically, generates AI-driven review narratives, and gives managers evidence-first calibration — all without adding burden to either side.
Performance reviews reward memory, not merit
"WorkMark was designed to replace memory-based performance evaluation with evidence-based work contributions, helping employees and managers understand impact clearly without increasing cognitive or political burden."
We conducted group interviews — one participant at a time
My task was to understand how employees and managers actually experience performance evaluation. Every session ran as a group interview: the whole team on the same call, interviewing one participant at a time.
What existing data confirmed
How the system actually works end-to-end
Before designing any screen, I mapped the full user journey — from login through contribution tracking, AI insight generation, and feedback loops.
Where WorkMark fits in the market
I mapped the competitive landscape to identify the positioning gap. Existing tools focus on recognition or evaluation — but none combine all three with an automated, continuous intelligence layer.
Two people. Same broken system.
Research crystallised into two distinct personas whose frustrations are mirror images — each a victim of the same structural gap.
- Work scattered across 4+ tools
- Cross-team contributions never surface
- Quiet work loses to high-drama moments
- No career growth narrative
- Ratings skew toward Q4 — Q1 disappears
- Calibration debates without shared data
- Can't advocate for quiet reports
- Time pressure forces shallow assessments
I built the wrong thing first. That was the real insight.
On Day 3 I led the team in designing a manager dashboard showing 12 employee variables. Managers stopped engaging by the third metric. I made the call: rebuild around 4 metrics with evidence links.
- Total task count across all tools
- Communication frequency score
- Peer mention rate in Slack
- Time-to-close on Jira tickets
- Cross-team collaboration graph
- Sentiment trend over quarters
- Documentation contribution index
- Code review participation rate
- Meeting attendance and engagement
- Manager 1:1 note consistency
- PR merge frequency and size
- Onboarding support hours given
One week. Five phases. One dead end that made it better.
The Hyper Hackathon gave me seven days — enough to go deep on research, hit a real dead end, make a hard call on Day 4, and ship a validated prototype.
Every decision was conscious
Five design principles — each chosen to resolve a specific tension between transparency, trust, and usability in an emotionally loaded product context.
Three layers. One coherent loop.
Signals flow from Slack, GitHub, Teams, Email, and Jira through webhooks into an aggregation hub, then through OAuth authentication and AI embeddings into summarised contribution intelligence.
Final Dashboard Interface
Everything converges here. Three primary flows — capture, review generation, and manager calibration — designed to be invisible in daily use, unmissably clear when it matters most.
The Final Dashboard Interface
Employees see their Performance Clarity Score, collaboration signals, and growth opportunities — in one calm, evidence-backed view.
The WorkMark identity — recognition, validation, impact
The WorkMark identity integrates a checkmark symbol representing recognition, validation, and measurable impact. Designed to feel credible in enterprise contexts while remaining human enough for ICs to trust it.
Day 7 validation. Unanimous response.
Eight participants — ICs and managers — walked through the full prototype. Structured walkthroughs, a SUS survey, and an open debrief.
We took this personally.
Every person on this team held a full-time job. Research happened after work. The pivot happened at 11 PM. The prototype was built on stolen evenings. This wasn't a hackathon exercise — it was a problem every one of us had lived.
What the project taught me
- The Day 4 pivot from 12 variables to 4 metrics was the best design decision I made. The failure was the breakthrough.
- Making employee data sovereignty non-negotiable from day one resolved every trust objection in testing.
- Group interviews — one participant at a time — gave us far richer data than individual sessions.
- I'd prototype the manager calibration view earlier — it's where the most complex design decisions live.
- I'd build a rough concept test for the employee consent flow before designing the full UI.
- I'd scope the integration layer more precisely — technically plausible but needs engineer validation.
