KNOWLEDGE SHARE PROGRESS DASHBOARD
JUNE 2024
OVERVIEW
Sugarwork helps teams capture tacit knowledge through guided conversations, creating resources like process maps and transition guides.
As adoption scaled, managers struggled to track the progress of knowledge-sharing initiatives scattered across emails, Slack messages, and spreadsheets.
I led the end-to-end design of a progress dashboard that centralised progress tracking, surfaced at-risk projects, and enabled faster, informed decision-making.
ROLE
Product Designer
Owned problem framing, user research and UX/UI design
Team
1 PM, 2 Developers, 1 QA
Duration
2 months
Initial Iterations to Production
IMPACT
72%
reduced oversight time
(4hrs to 60mins)
3X
faster identification of at-risk projects
30%
increase in knowledge sharing completion
The Problem
As Sugarwork grew from 3 to 15 teams and 200+ users, managers had to track critical knowledge across Slack, emails, spreadsheets, and the platform with no single source of truth.
DISCOVERY & Research
Interviewed managers across varying team sizes to understand how scale impacted oversight behaviors, and analyzed existing product, emails, and artifacts to map their real-world workflows.
Insight 1
Managers want a single source of truth
Insight 2
Managers needed a quick overview to take the next action
Defining Success
Research revealed three core needs: fast progress visibility, meaningful momentum signals, and scalable organization.
01
Viewers grasp the takeaway before they ever read the fine print.
02
Prioritize important information first, and drill into details only when needed
03
Numbers show movement and progress, not just where things happen to stand today.
Solution
Design decision 1
We explored both table and Kanban structures early in the design process.
Tables → high information density, low scannability
Kanban → lower density, faster pattern recognition
Table
High information density, Low scannability
Selected
Kanban
Lower density, Faster pattern recognition
Tradeoff: Reduced visible detail
To balance this, I introduced filtering by series (groups sharing the same template and output), allowing managers to quickly drill into relevant context without overwhelming the default view.
Design decision 2
We initially surfaced session counts and completion totals, but these only described the current status and did not show progress. I replaced them with three momentum signals: Hours recorded, Sessions this week and Recent activity
Together, these signals helped managers identify stalled projects sooner, shifting the dashboard from status reporting to decision-making tool.
Static Data
Dynamic Data and Actionable Inisghts
Selected
Design decision 3
As projects accumulated, completed and overdue sessions cluttered the dashboard, reducing visibility into active work. We considered archiving them, but that suggested the data was no longer relevant. Instead, I designed a Hide feature that cleared visual clutter while preserving historical data.
IMPACT
72%
reduced oversight time
(4hrs to 60mins)
3X
faster identification of at-risk projects
30%
increase in knowledge sharing completion
RESTROPECTIVE
Defining the Metrics
We measured impact through surveys and self-reported data, which worked, but left gaps. If I were doing this again, I'd define what we're tracking before we write a single line of code. Weekly active usage, time per session, how people engage with specific features.
Expand beyond a passive dashboard
The dashboard gave managers visibility into progress, but they still had to actively monitor it. Looking ahead, I'd explore proactive alerts, AI-generated summaries, and early risk signals that help managers spot stalled teams and take action sooner.
The value of the dashboard is not in the data it shows , it's in the decision it enables