Scanner Productivity
& Utilisation
Designing operational intelligence for radiology departments — transforming dense scanner data into decisions that move hospitals forward.
Hospitals had scanner data. Not scanner intelligence.
MRI and CT scanners are among the most expensive assets in a hospital — often running €1–3M per unit. Yet most radiology teams had no clear way to measure whether these systems were being fully utilized.
Operational data existed across systems, but it was fragmented, difficult to interpret, and entirely disconnected from the decisions users needed to make.
"The product showed numbers. Users needed clarity."
Are our scanners underutilized or overloaded?
Which systems are driving bottlenecks?
Where are we losing capacity?
How do we compare performance across sites?
Is downtime affecting our overall utilization rate?
Poor utilization creates a chain reaction across operations.
Delayed Appointments
Scheduling gaps compound into backlogs
Longer Wait Times
Patients wait longer for diagnostic imaging
Staff Overload
Technologists absorb scheduling inefficiency
Revenue Loss
Idle time on high-value assets hits P&L
No Visibility
Teams couldn't see the problem, let alone fix it
"We had spreadsheets, exports, and disconnected system logs. No single view of how our scanners were actually performing."
The existing product surfaced data. It didn't answer the operational questions users were actually asking.
Three roles. One shared need:
turn scanner data into operational decisions.
Radiology Head
Needs a high-level operational view across scanners, modalities, and sites to steer department strategy.
Operations Manager
Tracks scanner productivity day-to-day, managing schedules and optimizing throughput across the fleet.
Department Admin
Needs evidence for planning cycles, investment decisions, and reporting to hospital leadership.
We reframed the problem as a
decision-support challenge — not a reporting problem.
Discovery
- Stakeholder interviews
- Workflow observation
- Identifying operational blind spots
- Mapping decision journeys
Workflow Mapping
- How users answer scanner performance questions
- Where current tools failed
- Key metric hierarchies
- Critical decision moments
Dashboard Redesign
- KPI-first information architecture
- Layered drilldown flows
- Comparative benchmarking views
- Action-oriented visualizations
Validation
- Usability testing with operational users
- Speed-to-insight benchmarking
- Decision quality assessment
- Iterative refinement
From dense reporting to operational decision intelligence.
The redesign restructured the entire experience around a single principle: every screen should reduce uncertainty, not add to it.
We surfaced the most critical metrics upfront, built layered drilldowns for root-cause investigation, and designed visualizations that answered operational questions — not just displayed numbers.
① System-Wide Overview
Fleet-level KPIs, productivity trends, comparative benchmarks across all scanners and sites
② Site & Scanner Drilldown
Per-scanner productivity, exam volumes by procedure type, utilization breakdown by hour and day
③ Actionable Operational Insights
Anomaly detection, downtime patterns, scheduling gaps, and clear next steps for operational intervention
Single metric ranked across all scanners — outliers both high and low are immediately visible. No calculation required.
Contrast vs. non-contrast exam split surfaces protocol mix differences between scanners — a key signal for capacity planning.
Table / preparation / idle time as a stacked bar per scanner — instantly reveals where operational time is being lost.
Bar + trend-line combo surfaces the direction of performance change — not just a snapshot, but a trajectory users can act on.
Day-by-day usage heatmap reveals scheduling patterns, peak load times, and idle windows across the week at a glance.
Colour-coded by body part, the timeline makes density and gaps in exam flow immediately visible without reading numbers.
Three principles that shaped every screen.
Designed for fast scanning
Users needed to interpret scanner performance in seconds, not minutes. Dense operational data required ruthless hierarchy.
Designed for comparison
Operational decisions depend on relative performance. A number means nothing without context — the benchmark is everything.
Designed for action
The goal was never data consumption. It was operational intervention. Every screen was built to lead somewhere actionable.
A reporting tool became a decision-support product.
The redesign shifted the platform from a passive data interface to an active operational intelligence tool — one that hospitals could rely on to surface problems and support planning.
Radiology heads could identify underutilised scanners without manual data extraction
Downtime and idle-time patterns became visible across the fleet at a glance
Operations managers could benchmark scanner performance across sites in one view
Faster operational planning decisions backed by reliable visualised data
Department admins had clear evidence to support investment and maintenance decisions