Interactive Data Dashboard
Ran a large, multi-workstream healthcare integration program and built the live view that told stakeholders whether delivery was on track, whether issues were caught early, and what was driving them. One place to see where every workstream stood and what to fix next, instead of days-long manual status and defect reports.
Figures tagged Illustrative are representative examples that recreate the concept, not real data.
The business questions it answered
Leadership didn't need more data. They needed answers. I built the dashboard around the specific recurring questions stakeholders kept asking about delivery and quality:
"Are we keeping up? Are we closing bugs faster than we open them?"
"Are we catching issues early in review, or late from customers?"
"What are the top root-cause themes, and are they trending up?"
"How long are defects taking to close?"
"Where does every workstream stand, and what is blocked right now?"
How the program moved
Behind the metrics was the board that ran the work. Every integration workstream moved through one delivery lifecycle, from discovery through to live, each with an owner and a target. Blockers were not a stage. They were flagged on whatever stage a workstream sat in, so problems surfaced early and nothing stalled in silence.
~50
In flight
9
In QA
4
Blocked
Program roadmap
Core order & result flow
Inbound orders and outbound results live over the standard interface.
Scheduling & notes
Appointment sync and two-way clinical notes.
Self-serve provisioning
Partners onboard new connections without manual setup.
Modern standards & analytics
Move toward modern interoperability and richer reporting.
The operating cadence
The board was only as good as the rhythm behind it. As the program manager, I owned intake, kept the cross-functional view honest, drove blockers and dependencies to resolution, and reported on a steady cadence so stakeholders always knew where things stood.
Intake & prioritization
Sized incoming work against capacity and ranked it against program goals.
Cross-functional triage
Brought engineering, quality, and operations to one view of status and severity.
Dependency & blocker management
Tracked risks and dependencies, and drove blockers to an owner and a date.
Reporting cadence
Published a regular, self-serve status so stakeholders did not wait on a manual report.
From intake to insight
Every defect landed here first, tagged by where it came from and how urgent it was. This is the raw intake the dashboard below turned into trends: triaged on this board, measured in that one.
To triage
5Status not refreshing in portal after update
Report not generated on schedule
In progress
3Mapping mismatch on result import
Bulk download intermittently fails
In review
2Retry storm on upstream timeout
Notification not sent on later orders
The dashboard
Open defects
128
across all areas
Net this week
-6
closed > created
Early-detection
68%
caught in review
Median close
4.2d
time to resolve
Inflow vs outflow
trending_upAre we keeping up? Created vs closed per week.
Detection: early vs late
verifiedCatching issues before customers do.
trending_upEarly share up from 54% over the quarter.
Top root-cause themes
categoryThe metrics on the board
Representative metric set, recreated to show the approach.
Created vs closed
Net defect flow / week
Early-detection rate
% caught before customers
Root-cause mix
Top defect themes
Time to close
Median resolution time
How it changed decision-making
Before
Status and defect trends were assembled by hand and reviewed late. Blockers and problems were often noticed only after they had grown, and by the time a report landed, the moment to act had passed.
After
The team self-serves one live view of where delivery stands and what is breaking. Conversations shifted from "what is the status?" and "what broke?" to "are we on track, trending safe, and what do we fix next?"
Representative outcomes, recreated to show the shift.
Reporting turnaround
~[2–3] days to real-time
Early-detection rate
54% to 68%
On-time delivery
~[90]% on or ahead of target
What I would carry forward
Instrument earlier
The reporting view paid off most when it existed before the work scaled, not after. I would stand it up at the start next time.
Make blockers visible by default
Treating blocked as a flag on the real stage, not a stage of its own, kept the lifecycle honest and surfaced risk without hiding progress.
Let the team self-serve status
Once status was live and shared, my time moved from assembling reports to removing obstacles, which is where a program manager adds the most.