Workforce System Technology
Workforce management requires a comprehensive technology ecosystem for scalable, optimal operations. Key benefits of investing in workforce technology:
- Organizations can use technology platforms to clean up their data integrity by driving standardization of familiar workforce language/coding
- Technology can help organizations create one area for education management, skills and competency documentation, and licensure management with greater transparency
- Technology will drive huge wins with operational efficiency by automating redundant, manual processes that bog down frontline leaders
- The clean database achieved through technology will enable intelligent, data-driven insights for optimal workforce management in real time
Though implementing new technology can seem intimidating, the payoff from automated workforce management outweighs the effort.
Workforce System Technology Components
In addition to scheduling and staffing technology, these elements are necessary to create a comprehensive technology ecosystem:
- Human resources information systems (HRIS) house employee information such as job, licensure, certifications, and personal information, as well as organizational policies and reporting structure
- Learning management system offers virtual learning programs and keeps a record of completed programs that support competencies
- Scheduling and staffing technology supports functions such as building unit schedules, managing trades, offers, and open-shift claims, and facilitating day-of staffing activities
- Time and attendance technology manages daily worked shifts with timecard punches and appropriate coding
- Open shift recruitment technology automates the offering of unfilled shifts once the schedule is published
- Vendor management system (VMS) technology manages external labor (agency nurses) — source, obtain, validate credentials, offer the position, and deploy the nurse
Each of these elements is the source of truth for a specific area. In an ideal world, the HRIS and learning management system integrate with the scheduling and staffing system to auto-populate employees' licenses, certifications, and skills.
Choosing a Scheduling and Staffing System
Create criteria for measuring the performance of proposed systems before purchasing.
Ask for a full demonstration of the product and speak with other organizations who have implemented it. If the company is a start-up, consider a partnership to create and push the innovation forward.
Use these criteria to help ensure the technology platform meets your organization's needs:
Versatility
- Can the platform support both enterprise-wide operations and unit-specific needs?
- Is there potential growth and expansion in the future?
Flexibility
- Can the organization make changes so that the system better meets its unique needs?
User-friendly
- Can end-users easily navigate the platform?
Mobility
- Can end-users easily download the mobile option?
- Does the mobile option work on multiple types of devices?
- Does the mobile option offer robust features such as self-scheduling, viewing schedules, making trades, and signing up for extra shifts?
Integration
- Does the platform integrate with existing technology?
Functionality
- Does the platform automate scheduling and staffing work?
- Can the platform forecast future scheduling and staffing needs?
AI Capabilities to Evaluate
The next generation of workforce technology goes beyond automation to intelligence. When evaluating scheduling and staffing platforms, assess these AI capabilities:
- Predictive demand forecasting — Can the system predict patient census and staffing needs using historical data, seasonal patterns, and real-time inputs? Predictive models outperform static HPPD-based forecasts.
- Auto-balanced scheduling — Can the system automatically assign open shifts using constraint-based optimization that respects scheduling rules, preferences, and fairness? This replaces the manual "balancing act" that consumes manager time.
- Dynamic pricing — Can the system adjust incentive pricing for open shifts in real time based on fill probability, urgency, and clinician behavior? Dynamic pricing maximizes fill rates while minimizing spend.
- Preference learning — Does the system capture and learn clinician preferences — both stated (via self-service tools) and observed (from historical scheduling patterns and shift pickup behavior)?
- Continuous feedback loops — Does the system improve over time? Each scheduling period should serve as a data set that refines future predictions and scoring.
- Explainability — Can the system explain why it made a specific recommendation? Managers need to understand and trust AI outputs before adopting them.
When evaluating AI-powered scheduling technology, ask vendors:
- Does the system integrate with existing HRIS and scheduling platforms via API, or does it require a full system replacement?
- What data does the AI require, and how long does it take to produce meaningful results?
- Can the AI enforce organization-specific rules (union contracts, fatigue policies, certification requirements)?
- Does the system offer a "suggest and review" mode where managers approve AI recommendations before they are applied?
- What KPIs does the system measure (fill rate, FTE utilization, preference score, fairness)?
- Can the AI simulate schedule changes before committing them to the live system?
- What is the rollback process if AI-generated assignments need to be reversed?
Implementing the System
Investing in implementation and configuration is as important as buying the technology itself. Budget for the people and time needed for successful rollout, and designate "super users" who can advocate for the system and support others.