From 40% Short-Staffed to Fully Staffed: How RosterLab Helped Radiology Retain Staff

TL;DR

• An Auckland-based radiology department moved away from Excel rostering after 20 years to use a dedicated rostering platform.
• 40% short-staffed - now consistently fully staffed for the first time in 28 years with RosterLab
• Reduced rostering time from 120 hours to just 8 hours per month (based on a 4 week roster)
• $80,000+ per year in savings
• Over 600 preferences met per roster period
• Zero breaches of MECA rules

Background

A radiology department based in Auckland had been using Excel spreadsheets for its rostering for more than 20 years. With multiple modalities, including general X-ray, CT, MRI, interventional, theatre, and cath lab, managing staff with varying skill sets across shifts was increasingly complex.

The department’s MRT team leader explains, “Radiology is unique… staff have their base skill, which is usually general X-ray, and then they have their speciality skills…there's just so many different skill sets that we need to ensure coverage for." 

The department also faced strict compliance requirements with two MECAs (Multi-Employer Collective Agreements) that dictated maximum working days and weekend restrictions, adding to its complexity.

The Challenge

By 2022, the department faced a critical staffing crisis:

• 40% staff shortage - struggling to cover all shifts and services
• Manual rostering was consuming 30 hours per week, requiring multiple staff (typically 15 changes per day to the roster with five people involved)
• High scheduling error risks and compliance breaches ($250 penalties per breach)
• Challenges with staff retention - new graduates were leaving within 6 months
• Lack of visibility for staff on upcoming shifts or who they’d be working with
• System fragility - if any rostering staff were absent, "the whole system collapsed".

Reflecting on the impact, the team lead explains, "We got to the point in 2022 where we were almost 40% down on staff and still trying to cover all services and keep all departments working." 

On top of these staffing challenges, radiology rosters are generally more complex:

• Multiple skill requirements per shift: they need to ensure each area has staff with the right qualifications
• Overlapping capabilities: some staff can work in multiple areas, others can't
• Specific procedure requirements: different imaging procedures require different certifications
• Coverage across all services: they must ensure all departments and procedures have qualified staff

"To do one roster was taking us about 30 hours per week... somebody has to input all of our staff's annual leave and process all their requests and then work out according to our MECA, who can work a shift.…we were expected to put the roster out at least 6 weeks in advance - we would really struggle"

The RosterLab Solution

After discovering RosterLab at an NZIMRT conference, the department was keen to implement the AI-powered rostering system.

The implementation included:

• Automated roster generation ensuring MECA compliance
• Maximising coverage based on skills
• Staff preference system through our mobile app
• Real-time visibility of shifts and colleagues
• Easy onboarding for new staff
• Automatic conflict resolution

This complexity is why RosterLab was so valuable - it could automatically solve this multi-dimensional puzzle of matching staff skills to departmental needs while respecting all the compliance rules and preferences.

"It was just so easy to load in a new staff member. It was as simple as providing the member of staff the roster in advance, downloading the app, and there the roster is. The business case was very much in favour of using it. Just the time and cost savings alone were very much in favour of using RosterLab" said the MRT lead.

Ongoing Benefits

Reflecting on the benefits, the MRT lead explains, “We are now fully staffed... I've been here for 28 years, and we've never managed to achieve this level of staffing consistently for more than 2 months until RosterLab"

The results were transformative:

• Time savings: reduced from 120 hours to just 8 hours per month
• Staff retention: improved from 40% shortage to fully staffed
• Financial savings: estimated $80,000+ per year in savings (enough to hire another member of staff)
• Staff satisfaction: over 600 preferences met per roster period
• Compliance: zero breaches of MECA rules
• Trust: after trialling three roster iterations (across 12 weeks), complete confidence in the system
• Retained knowledge: the system preserved rostering knowledge, so anyone could step in when regular staff were away.

"The main advantage that we found is that you can generate the roster automatically, but you can also switch roster views by employee and by shift, making it easier to manage - that is what the staff loved. We trust it. It's made management's life easier."

The department continues using RosterLab for roster generation because the alternative, returning to Excel, is “unthinkable”.

Why This Matters

This Auckland radiography department’s experience demonstrates how intelligent rostering technology can solve even the most complex scheduling challenges in healthcare. The dramatic improvement in staff retention alone justifies the investment, while the time savings allow managers to focus on patient care rather than administrative tasks.

"It has managed to solve what I would say is one of the most complex rosters... and one of the biggest problems for us." said the MRT lead.

The case powerfully illustrates that when staff have input into their schedules through preferences, and when compliance is automatically managed, both retention and satisfaction dramatically improve - creating a virtuous cycle that benefits patients, staff, and the healthcare system.

If you’d like to learn how we can help your team with their staff roster, book a demo with us to experience modern workforce management.

"If you can save time, particularly in the public healthcare sector, that's equal to money and that means more patients that you can help. So it's a win all round."